mirror of
https://github.com/oobabooga/text-generation-webui.git
synced 2024-11-25 17:29:22 +01:00
Merge branch 'oobabooga:dev' into dev
This commit is contained in:
Artificiangel
GitHub
commit
dceb23c763
1
.github/dependabot.yml
vendored
1
.github/dependabot.yml
vendored
@ -7,5 +7,6 @@ version: 2
|
||||
updates:
|
||||
- package-ecosystem: "pip" # See documentation for possible values
|
||||
directory: "/" # Location of package manifests
|
||||
target-branch: "dev"
|
||||
schedule:
|
||||
interval: "weekly"
|
||||
|
||||
4
.github/workflows/stale.yml
vendored
4
.github/workflows/stale.yml
vendored
@ -13,8 +13,8 @@ jobs:
|
||||
- uses: actions/stale@v5
|
||||
with:
|
||||
stale-issue-message: ""
|
||||
close-issue-message: "This issue has been closed due to inactivity for 2 months. If you believe it is still relevant, please leave a comment below. You can tag a developer in your comment."
|
||||
days-before-issue-stale: 60
|
||||
close-issue-message: "This issue has been closed due to inactivity for 6 months. If you believe it is still relevant, please leave a comment below. You can tag a developer in your comment."
|
||||
days-before-issue-stale: 180
|
||||
days-before-issue-close: 0
|
||||
stale-issue-label: "stale"
|
||||
days-before-pr-stale: -1
|
||||
|
||||
29
README.md
29
README.md
@ -11,7 +11,7 @@ Its goal is to become the [AUTOMATIC1111/stable-diffusion-webui](https://github.
|
||||
## Features
|
||||
|
||||
* 3 interface modes: default (two columns), notebook, and chat.
|
||||
* Multiple model backends: [Transformers](https://github.com/huggingface/transformers), [llama.cpp](https://github.com/ggerganov/llama.cpp) (through [llama-cpp-python](https://github.com/abetlen/llama-cpp-python)), [ExLlamaV2](https://github.com/turboderp/exllamav2), [AutoGPTQ](https://github.com/PanQiWei/AutoGPTQ), [AutoAWQ](https://github.com/casper-hansen/AutoAWQ).
|
||||
* Multiple model backends: [Transformers](https://github.com/huggingface/transformers), [llama.cpp](https://github.com/ggerganov/llama.cpp) (through [llama-cpp-python](https://github.com/abetlen/llama-cpp-python)), [ExLlamaV2](https://github.com/turboderp/exllamav2), [AutoGPTQ](https://github.com/PanQiWei/AutoGPTQ), [AutoAWQ](https://github.com/casper-hansen/AutoAWQ), [TensorRT-LLM](https://github.com/NVIDIA/TensorRT-LLM).
|
||||
* Dropdown menu for quickly switching between different models.
|
||||
* Large number of extensions (built-in and user-contributed), including Coqui TTS for realistic voice outputs, Whisper STT for voice inputs, translation, [multimodal pipelines](https://github.com/oobabooga/text-generation-webui/tree/main/extensions/multimodal), vector databases, Stable Diffusion integration, and a lot more. See [the wiki](https://github.com/oobabooga/text-generation-webui/wiki/07-%E2%80%90-Extensions) and [the extensions directory](https://github.com/oobabooga/text-generation-webui-extensions) for details.
|
||||
* [Chat with custom characters](https://github.com/oobabooga/text-generation-webui/wiki/03-%E2%80%90-Parameters-Tab#character).
|
||||
@ -76,12 +76,12 @@ conda activate textgen
|
||||
|
||||
| System | GPU | Command |
|
||||
|--------|---------|---------|
|
||||
| Linux/WSL | NVIDIA | `pip3 install torch==2.2.1 torchvision==0.17.1 torchaudio==2.2.1 --index-url https://download.pytorch.org/whl/cu121` |
|
||||
| Linux/WSL | CPU only | `pip3 install torch==2.2.1 torchvision==0.17.1 torchaudio==2.2.1 --index-url https://download.pytorch.org/whl/cpu` |
|
||||
| Linux | AMD | `pip3 install torch==2.2.1 torchvision==0.17.1 torchaudio==2.2.1 --index-url https://download.pytorch.org/whl/rocm5.6` |
|
||||
| MacOS + MPS | Any | `pip3 install torch==2.2.1 torchvision==0.17.1 torchaudio==2.2.1` |
|
||||
| Windows | NVIDIA | `pip3 install torch==2.2.1 torchvision==0.17.1 torchaudio==2.2.1 --index-url https://download.pytorch.org/whl/cu121` |
|
||||
| Windows | CPU only | `pip3 install torch==2.2.1 torchvision==0.17.1 torchaudio==2.2.1` |
|
||||
| Linux/WSL | NVIDIA | `pip3 install torch==2.2.2 torchvision==0.17.2 torchaudio==2.2.2 --index-url https://download.pytorch.org/whl/cu121` |
|
||||
| Linux/WSL | CPU only | `pip3 install torch==2.2.2 torchvision==0.17.2 torchaudio==2.2.2 --index-url https://download.pytorch.org/whl/cpu` |
|
||||
| Linux | AMD | `pip3 install torch==2.2.2 torchvision==0.17.2 torchaudio==2.2.2 --index-url https://download.pytorch.org/whl/rocm5.6` |
|
||||
| MacOS + MPS | Any | `pip3 install torch==2.2.2 torchvision==0.17.2 torchaudio==2.2.2` |
|
||||
| Windows | NVIDIA | `pip3 install torch==2.2.2 torchvision==0.17.2 torchaudio==2.2.2 --index-url https://download.pytorch.org/whl/cu121` |
|
||||
| Windows | CPU only | `pip3 install torch==2.2.2 torchvision==0.17.2 torchaudio==2.2.2` |
|
||||
|
||||
The up-to-date commands can be found here: https://pytorch.org/get-started/locally/.
|
||||
|
||||
@ -146,7 +146,7 @@ Then browse to
|
||||
1) For Kepler GPUs and older, you will need to install CUDA 11.8 instead of 12:
|
||||
|
||||
```
|
||||
pip3 install torch==2.2.1 torchvision==0.17.1 torchaudio==2.2.1 --index-url https://download.pytorch.org/whl/cu118
|
||||
pip3 install torch==2.2.2 torchvision==0.17.2 torchaudio==2.2.2 --index-url https://download.pytorch.org/whl/cu118
|
||||
conda install -y -c "nvidia/label/cuda-11.8.0" cuda-runtime
|
||||
```
|
||||
|
||||
@ -392,15 +392,18 @@ Run `python download-model.py --help` to see all the options.
|
||||
|
||||
https://colab.research.google.com/github/oobabooga/text-generation-webui/blob/main/Colab-TextGen-GPU.ipynb
|
||||
|
||||
## Contributing
|
||||
## Acknowledgment
|
||||
|
||||
If you would like to contribute to the project, check out the [Contributing guidelines](https://github.com/oobabooga/text-generation-webui/wiki/Contributing-guidelines).
|
||||
In August 2023, [Andreessen Horowitz](https://a16z.com/) (a16z) provided a generous grant to encourage and support my independent work on this project. I am **extremely** grateful for their trust and recognition.
|
||||
|
||||
## Community
|
||||
## Links
|
||||
|
||||
#### Community
|
||||
|
||||
* Subreddit: https://www.reddit.com/r/oobabooga/
|
||||
* Discord: https://discord.gg/jwZCF2dPQN
|
||||
|
||||
## Acknowledgment
|
||||
#### Support
|
||||
|
||||
In August 2023, [Andreessen Horowitz](https://a16z.com/) (a16z) provided a generous grant to encourage and support my independent work on this project. I am **extremely** grateful for their trust and recognition.
|
||||
* ko-fi: https://ko-fi.com/oobabooga
|
||||
* GitHub Sponsors: https://github.com/sponsors/oobabooga
|
||||
|
||||
@ -49,7 +49,7 @@
|
||||
|
||||
.gradio-container .chat .assistant-message {
|
||||
padding: 20px;
|
||||
background: var(--color-grey-200);
|
||||
background: #f4f4f4;
|
||||
margin-top: 9px !important;
|
||||
margin-bottom: 12px !important;
|
||||
border-radius: 7px;
|
||||
@ -62,8 +62,8 @@
|
||||
|
||||
.gradio-container .chat .user-message {
|
||||
padding: 20px;
|
||||
padding-left: 0px;
|
||||
padding-right: 0px;
|
||||
padding-left: 0;
|
||||
padding-right: 0;
|
||||
background-color: transparent;
|
||||
border-radius: 8px;
|
||||
border-bottom-right-radius: 0;
|
||||
|
||||
68
css/main.css
68
css/main.css
@ -95,8 +95,8 @@ gradio-app > :first-child {
|
||||
}
|
||||
|
||||
.header_bar {
|
||||
background-color: #f7f7f7;
|
||||
box-shadow: 0 0px 3px rgba(22 22 22 / 35%);
|
||||
background-color: #f4f4f4;
|
||||
box-shadow: 0 0 3px rgba(22 22 22 / 35%);
|
||||
margin-bottom: 0;
|
||||
overflow-x: scroll;
|
||||
margin-left: calc(-1 * var(--size-4));
|
||||
@ -221,6 +221,7 @@ button {
|
||||
|
||||
.pretty_scrollbar::-webkit-scrollbar {
|
||||
width: 7px;
|
||||
height: 7px;
|
||||
}
|
||||
|
||||
.pretty_scrollbar::-webkit-scrollbar-track {
|
||||
@ -245,6 +246,10 @@ button {
|
||||
background: #374151;
|
||||
}
|
||||
|
||||
.pretty_scrollbar::-webkit-scrollbar-corner {
|
||||
background: transparent;
|
||||
}
|
||||
|
||||
audio {
|
||||
max-width: 100%;
|
||||
}
|
||||
@ -331,6 +336,11 @@ div.svelte-362y77>*, div.svelte-362y77>.form>* {
|
||||
padding-left: 0;
|
||||
padding-right: 0;
|
||||
}
|
||||
|
||||
.chat {
|
||||
padding-left: 0;
|
||||
padding-right: 0;
|
||||
}
|
||||
}
|
||||
|
||||
.chat {
|
||||
@ -386,7 +396,7 @@ div.svelte-362y77>*, div.svelte-362y77>.form>* {
|
||||
|
||||
.chat .message:last-child {
|
||||
margin-bottom: 0 !important;
|
||||
padding-bottom: 0 !important;
|
||||
padding-bottom: 15px !important;
|
||||
}
|
||||
|
||||
.message-body li {
|
||||
@ -433,12 +443,12 @@ div.svelte-362y77>*, div.svelte-362y77>.form>* {
|
||||
.message-body code {
|
||||
white-space: pre-wrap !important;
|
||||
word-wrap: break-word !important;
|
||||
border: 1px solid #666666;
|
||||
border: 1px solid #666;
|
||||
border-radius: 5px;
|
||||
font-size: 82%;
|
||||
padding: 1px 3px;
|
||||
background: #0d1117 !important;
|
||||
color: rgb(201, 209, 217);
|
||||
color: rgb(201 209 217);
|
||||
}
|
||||
|
||||
.message-body pre > code {
|
||||
@ -505,7 +515,7 @@ div.svelte-362y77>*, div.svelte-362y77>.form>* {
|
||||
#show-controls {
|
||||
position: absolute;
|
||||
height: 100%;
|
||||
background-color: var(--background-fill-primary);
|
||||
background-color: transparent;
|
||||
border: 0 !important;
|
||||
border-radius: 0;
|
||||
}
|
||||
@ -695,7 +705,7 @@ div.svelte-362y77>*, div.svelte-362y77>.form>* {
|
||||
@media screen and (width >= 1327px) {
|
||||
#past-chats-row {
|
||||
position: absolute;
|
||||
top: 16px;
|
||||
top: 36px;
|
||||
left: 0;
|
||||
width: calc(0.5*(var(--document-width) - 880px - 120px - 16px*2));
|
||||
max-width: 300px;
|
||||
@ -743,3 +753,47 @@ div.svelte-362y77>*, div.svelte-362y77>.form>* {
|
||||
display: none;
|
||||
}
|
||||
}
|
||||
|
||||
#past-chats {
|
||||
max-height: calc(100vh - 195px);
|
||||
overflow-y: scroll !important;
|
||||
border-radius: 0;
|
||||
scrollbar-width: none; /* Hide scrollbar in Firefox by default */
|
||||
}
|
||||
|
||||
#past-chats label {
|
||||
width: 100%;
|
||||
background-color: transparent !important;
|
||||
background: none;
|
||||
border: 0;
|
||||
border-radius: 0;
|
||||
padding-top: 8px;
|
||||
padding-bottom: 8px;
|
||||
}
|
||||
|
||||
#past-chats > :nth-child(2) {
|
||||
display: none;
|
||||
}
|
||||
|
||||
#past-chats > :nth-child(3) {
|
||||
gap: 0;
|
||||
}
|
||||
|
||||
#past-chats::-webkit-scrollbar {
|
||||
display: none;
|
||||
}
|
||||
|
||||
#past-chats:hover {
|
||||
scrollbar-width: auto;
|
||||
}
|
||||
|
||||
#past-chats:hover::-webkit-scrollbar {
|
||||
display: block;
|
||||
}
|
||||
|
||||
@media screen and (width < 1327px) {
|
||||
#past-chats {
|
||||
max-height: 300px;
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
27
docker/TensorRT-LLM/Dockerfile
Normal file
27
docker/TensorRT-LLM/Dockerfile
Normal file
@ -0,0 +1,27 @@
|
||||
FROM pytorch/pytorch:2.2.1-cuda12.1-cudnn8-runtime
|
||||
|
||||
# Install Git
|
||||
RUN apt update && apt install -y git
|
||||
|
||||
# System-wide TensorRT-LLM requirements
|
||||
RUN apt install -y openmpi-bin libopenmpi-dev
|
||||
|
||||
# Set the working directory
|
||||
WORKDIR /app
|
||||
|
||||
# Install text-generation-webui
|
||||
RUN git clone https://github.com/oobabooga/text-generation-webui
|
||||
WORKDIR /app/text-generation-webui
|
||||
RUN pip install -r requirements.txt
|
||||
|
||||
# This is needed to avoid an error about "Failed to build mpi4py" in the next command
|
||||
ENV LD_LIBRARY_PATH=/usr/lib/x86_64-linux-gnu:$LD_LIBRARY_PATH
|
||||
|
||||
# Install TensorRT-LLM
|
||||
RUN pip3 install tensorrt_llm==0.10.0 -U --pre --extra-index-url https://pypi.nvidia.com
|
||||
|
||||
# Expose the necessary port for the Python server
|
||||
EXPOSE 7860 5000
|
||||
|
||||
# Run the Python server.py script with the specified command
|
||||
CMD ["python", "server.py", "--api", "--listen"]
|
||||
@ -18,13 +18,13 @@ In the **Prompt** menu, you can select from some predefined prompts defined unde
|
||||
|
||||
### Output
|
||||
|
||||
Four tabs can be found:
|
||||
Five tabs can be found:
|
||||
|
||||
* **Raw**: where the raw text generated by the model appears.
|
||||
* **Markdown**: it contains a "Render" button. You can click on it at any time to render the current output as markdown. This is particularly useful for models that generate LaTeX equations like GALACTICA.
|
||||
* **HTML**: displays the output in an HTML style that is meant to be easier to read. Its style is defined under `text-generation-webui/css/html_readable_style.css`.
|
||||
* **Logits**: when you click on "Get next token probabilities", this tab displays the 50 most likely next tokens and their probabilities based on your current input. If "Use samplers" is checked, the probabilities will be the ones after the sampling parameters in the "Parameters" > "Generation" tab are applied. Otherwise, they will be the raw probabilities generated by the model.
|
||||
* **Tokens**: allows you to tokenize your prompt and see the ID numbers for the individuals tokens.
|
||||
* **Tokens**: allows you to tokenize your prompt and see the ID numbers for the individual tokens.
|
||||
|
||||
## Notebook tab
|
||||
|
||||
|
||||
@ -219,7 +219,7 @@ print()
|
||||
|
||||
### Environment variables
|
||||
|
||||
The following environment variables can be used (they take precendence over everything else):
|
||||
The following environment variables can be used (they take precedence over everything else):
|
||||
|
||||
| Variable Name | Description | Example Value |
|
||||
|------------------------|------------------------------------|----------------------------|
|
||||
|
||||
@ -1,4 +1,4 @@
|
||||
These files is a mirror of the documentation at:
|
||||
These files are a mirror of the documentation at:
|
||||
|
||||
# https://github.com/oobabooga/text-generation-webui/wiki
|
||||
|
||||
|
||||
@ -33,7 +33,7 @@ params = {
|
||||
'hr_upscaler': 'ESRGAN_4x',
|
||||
'hr_scale': '1.0',
|
||||
'seed': -1,
|
||||
'sampler_name': 'DPM++ 2M Karras',
|
||||
'sampler_name': 'DPM++ 2M',
|
||||
'steps': 32,
|
||||
'cfg_scale': 7,
|
||||
'textgen_prefix': 'Please provide a detailed and vivid description of [subject]',
|
||||
|
||||
86
extensions/whisper_stt/script.js
Normal file
86
extensions/whisper_stt/script.js
Normal file
@ -0,0 +1,86 @@
|
||||
console.log("Whisper STT script loaded");
|
||||
|
||||
let mediaRecorder;
|
||||
let audioChunks = [];
|
||||
let isRecording = false;
|
||||
|
||||
window.startStopRecording = function() {
|
||||
if (!navigator.mediaDevices || !navigator.mediaDevices.getUserMedia) {
|
||||
console.error("getUserMedia not supported on your browser!");
|
||||
return;
|
||||
}
|
||||
|
||||
if (isRecording == false) {
|
||||
//console.log("Start recording function called");
|
||||
navigator.mediaDevices.getUserMedia({ audio: true })
|
||||
.then(stream => {
|
||||
//console.log("Got audio stream");
|
||||
mediaRecorder = new MediaRecorder(stream);
|
||||
audioChunks = []; // Reset audio chunks
|
||||
mediaRecorder.start();
|
||||
//console.log("MediaRecorder started");
|
||||
recButton.icon;
|
||||
recordButton.innerHTML = recButton.innerHTML = "Stop";
|
||||
isRecording = true;
|
||||
|
||||
mediaRecorder.addEventListener("dataavailable", event => {
|
||||
//console.log("Data available event, data size: ", event.data.size);
|
||||
audioChunks.push(event.data);
|
||||
});
|
||||
|
||||
mediaRecorder.addEventListener("stop", () => {
|
||||
//console.log("MediaRecorder stopped");
|
||||
if (audioChunks.length > 0) {
|
||||
const audioBlob = new Blob(audioChunks, { type: "audio/webm" });
|
||||
//console.log("Audio blob created, size: ", audioBlob.size);
|
||||
const reader = new FileReader();
|
||||
reader.readAsDataURL(audioBlob);
|
||||
reader.onloadend = function() {
|
||||
const base64data = reader.result;
|
||||
//console.log("Audio converted to base64, length: ", base64data.length);
|
||||
|
||||
const audioBase64Input = document.querySelector("#audio-base64 textarea");
|
||||
if (audioBase64Input) {
|
||||
audioBase64Input.value = base64data;
|
||||
audioBase64Input.dispatchEvent(new Event("input", { bubbles: true }));
|
||||
audioBase64Input.dispatchEvent(new Event("change", { bubbles: true }));
|
||||
//console.log("Updated textarea with base64 data");
|
||||
} else {
|
||||
console.error("Could not find audio-base64 textarea");
|
||||
}
|
||||
};
|
||||
} else {
|
||||
console.error("No audio data recorded for Whisper");
|
||||
}
|
||||
});
|
||||
});
|
||||
} else {
|
||||
//console.log("Stopping MediaRecorder");
|
||||
recordButton.innerHTML = recButton.innerHTML = "Rec.";
|
||||
isRecording = false;
|
||||
mediaRecorder.stop();
|
||||
}
|
||||
};
|
||||
|
||||
const recordButton = gradioApp().querySelector("#record-button");
|
||||
recordButton.addEventListener("click", window.startStopRecording);
|
||||
|
||||
|
||||
function gradioApp() {
|
||||
const elems = document.getElementsByTagName("gradio-app");
|
||||
const gradioShadowRoot = elems.length == 0 ? null : elems[0].shadowRoot;
|
||||
return gradioShadowRoot ? gradioShadowRoot : document;
|
||||
}
|
||||
|
||||
|
||||
// extra rec button next to generate button
|
||||
var recButton = recordButton.cloneNode(true);
|
||||
var generate_button = document.getElementById("Generate");
|
||||
generate_button.insertAdjacentElement("afterend", recButton);
|
||||
|
||||
recButton.style.setProperty("margin-left", "-10px");
|
||||
recButton.innerHTML = "Rec.";
|
||||
|
||||
recButton.addEventListener("click", function() {
|
||||
recordButton.click();
|
||||
});
|
||||
@ -1,5 +1,13 @@
|
||||
import base64
|
||||
import gc
|
||||
import io
|
||||
from pathlib import Path
|
||||
|
||||
import gradio as gr
|
||||
import speech_recognition as sr
|
||||
import numpy as np
|
||||
import torch
|
||||
import whisper
|
||||
from pydub import AudioSegment
|
||||
|
||||
from modules import shared
|
||||
|
||||
@ -8,13 +16,16 @@ input_hijack = {
|
||||
'value': ["", ""]
|
||||
}
|
||||
|
||||
# parameters which can be customized in settings.json of webui
|
||||
# parameters which can be customized in settings.yaml of webui
|
||||
params = {
|
||||
'whipser_language': 'english',
|
||||
'whipser_model': 'small.en',
|
||||
'auto_submit': True
|
||||
}
|
||||
|
||||
startup_device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
|
||||
WHISPERMODEL = whisper.load_model(params['whipser_model'], device=startup_device)
|
||||
|
||||
|
||||
def chat_input_modifier(text, visible_text, state):
|
||||
global input_hijack
|
||||
@ -25,47 +36,84 @@ def chat_input_modifier(text, visible_text, state):
|
||||
return text, visible_text
|
||||
|
||||
|
||||
def do_stt(audio, whipser_model, whipser_language):
|
||||
transcription = ""
|
||||
r = sr.Recognizer()
|
||||
def do_stt(audio, whipser_language):
|
||||
# use pydub to convert sample_rate and sample_width for whisper input
|
||||
dubaudio = AudioSegment.from_file(io.BytesIO(audio))
|
||||
dubaudio = dubaudio.set_channels(1)
|
||||
dubaudio = dubaudio.set_frame_rate(16000)
|
||||
dubaudio = dubaudio.set_sample_width(2)
|
||||
|
||||
# Convert to AudioData
|
||||
audio_data = sr.AudioData(sample_rate=audio[0], frame_data=audio[1], sample_width=4)
|
||||
# same method to get the array as openai whisper repo used from wav file
|
||||
audio_np = np.frombuffer(dubaudio.raw_data, np.int16).flatten().astype(np.float32) / 32768.0
|
||||
|
||||
try:
|
||||
transcription = r.recognize_whisper(audio_data, language=whipser_language, model=whipser_model)
|
||||
except sr.UnknownValueError:
|
||||
print("Whisper could not understand audio")
|
||||
except sr.RequestError as e:
|
||||
print("Could not request results from Whisper", e)
|
||||
if len(whipser_language) == 0:
|
||||
result = WHISPERMODEL.transcribe(audio=audio_np)
|
||||
else:
|
||||
result = WHISPERMODEL.transcribe(audio=audio_np, language=whipser_language)
|
||||
return result["text"]
|
||||
|
||||
|
||||
def auto_transcribe(audio, auto_submit, whipser_language):
|
||||
if audio is None or audio == "":
|
||||
print("Whisper received no audio data")
|
||||
return "", ""
|
||||
audio_bytes = base64.b64decode(audio.split(',')[1])
|
||||
|
||||
transcription = do_stt(audio_bytes, whipser_language)
|
||||
if auto_submit:
|
||||
input_hijack.update({"state": True, "value": [transcription, transcription]})
|
||||
return transcription
|
||||
|
||||
|
||||
def auto_transcribe(audio, auto_submit, whipser_model, whipser_language):
|
||||
if audio is None:
|
||||
return "", ""
|
||||
transcription = do_stt(audio, whipser_model, whipser_language)
|
||||
if auto_submit:
|
||||
input_hijack.update({"state": True, "value": [transcription, transcription]})
|
||||
def reload_whispermodel(whisper_model_name: str, whisper_language: str, device: str):
|
||||
if len(whisper_model_name) > 0:
|
||||
global WHISPERMODEL
|
||||
WHISPERMODEL = None
|
||||
if torch.cuda.is_available():
|
||||
torch.cuda.empty_cache()
|
||||
gc.collect()
|
||||
|
||||
return transcription, None
|
||||
if device != "none":
|
||||
if device == "cuda":
|
||||
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
|
||||
|
||||
WHISPERMODEL = whisper.load_model(whisper_model_name, device=device)
|
||||
params.update({"whipser_model": whisper_model_name})
|
||||
if ".en" in whisper_model_name:
|
||||
whisper_language = "english"
|
||||
audio_update = gr.Audio.update(interactive=True)
|
||||
else:
|
||||
audio_update = gr.Audio.update(interactive=False)
|
||||
return [whisper_model_name, whisper_language, str(device), audio_update]
|
||||
|
||||
|
||||
def ui():
|
||||
with gr.Accordion("Whisper STT", open=True):
|
||||
with gr.Row():
|
||||
audio = gr.Audio(source="microphone")
|
||||
audio = gr.Textbox(elem_id="audio-base64", visible=False)
|
||||
record_button = gr.Button("Rec.", elem_id="record-button", elem_classes="custom-button")
|
||||
with gr.Row():
|
||||
with gr.Accordion("Settings", open=False):
|
||||
auto_submit = gr.Checkbox(label='Submit the transcribed audio automatically', value=params['auto_submit'])
|
||||
whipser_model = gr.Dropdown(label='Whisper Model', value=params['whipser_model'], choices=["tiny.en", "base.en", "small.en", "medium.en", "tiny", "base", "small", "medium", "large"])
|
||||
whipser_language = gr.Dropdown(label='Whisper Language', value=params['whipser_language'], choices=["chinese", "german", "spanish", "russian", "korean", "french", "japanese", "portuguese", "turkish", "polish", "catalan", "dutch", "arabic", "swedish", "italian", "indonesian", "hindi", "finnish", "vietnamese", "hebrew", "ukrainian", "greek", "malay", "czech", "romanian", "danish", "hungarian", "tamil", "norwegian", "thai", "urdu", "croatian", "bulgarian", "lithuanian", "latin", "maori", "malayalam", "welsh", "slovak", "telugu", "persian", "latvian", "bengali", "serbian", "azerbaijani", "slovenian", "kannada", "estonian", "macedonian", "breton", "basque", "icelandic", "armenian", "nepali", "mongolian", "bosnian", "kazakh", "albanian", "swahili", "galician", "marathi", "punjabi", "sinhala", "khmer", "shona", "yoruba", "somali", "afrikaans", "occitan", "georgian", "belarusian", "tajik", "sindhi", "gujarati", "amharic", "yiddish", "lao", "uzbek", "faroese", "haitian creole", "pashto", "turkmen", "nynorsk", "maltese", "sanskrit", "luxembourgish", "myanmar", "tibetan", "tagalog", "malagasy", "assamese", "tatar", "hawaiian", "lingala", "hausa", "bashkir", "javanese", "sundanese"])
|
||||
device_dropd = gr.Dropdown(label='Device', value=str(startup_device), choices=["cuda", "cpu", "none"])
|
||||
whisper_model_dropd = gr.Dropdown(label='Whisper Model', value=params['whipser_model'], choices=["tiny.en", "base.en", "small.en", "medium.en", "tiny", "base", "small", "medium", "large"])
|
||||
whisper_language = gr.Dropdown(label='Whisper Language', value=params['whipser_language'], choices=["english", "chinese", "german", "spanish", "russian", "korean", "french", "japanese", "portuguese", "turkish", "polish", "catalan", "dutch", "arabic", "swedish", "italian", "indonesian", "hindi", "finnish", "vietnamese", "hebrew", "ukrainian", "greek", "malay", "czech", "romanian", "danish", "hungarian", "tamil", "norwegian", "thai", "urdu", "croatian", "bulgarian", "lithuanian", "latin", "maori", "malayalam", "welsh", "slovak", "telugu", "persian", "latvian", "bengali", "serbian", "azerbaijani", "slovenian", "kannada", "estonian", "macedonian", "breton", "basque", "icelandic", "armenian", "nepali", "mongolian", "bosnian", "kazakh", "albanian", "swahili", "galician", "marathi", "punjabi", "sinhala", "khmer", "shona", "yoruba", "somali", "afrikaans", "occitan", "georgian", "belarusian", "tajik", "sindhi", "gujarati", "amharic", "yiddish", "lao", "uzbek", "faroese", "haitian creole", "pashto", "turkmen", "nynorsk", "maltese", "sanskrit", "luxembourgish", "myanmar", "tibetan", "tagalog", "malagasy", "assamese", "tatar", "hawaiian", "lingala", "hausa", "bashkir", "javanese", "sundanese"])
|
||||
|
||||
audio.stop_recording(
|
||||
auto_transcribe, [audio, auto_submit, whipser_model, whipser_language], [shared.gradio['textbox'], audio]).then(
|
||||
None, auto_submit, None, js="(check) => {if (check) { document.getElementById('Generate').click() }}")
|
||||
audio.change(
|
||||
auto_transcribe, [audio, auto_submit, whisper_language], [shared.gradio['textbox']]).then(
|
||||
None, auto_submit, None, _js="(check) => {if (check) { document.getElementById('Generate').click() }}")
|
||||
|
||||
whipser_model.change(lambda x: params.update({"whipser_model": x}), whipser_model, None)
|
||||
whipser_language.change(lambda x: params.update({"whipser_language": x}), whipser_language, None)
|
||||
device_dropd.input(reload_whispermodel, [whisper_model_dropd, whisper_language, device_dropd], [whisper_model_dropd, whisper_language, device_dropd, audio])
|
||||
whisper_model_dropd.change(reload_whispermodel, [whisper_model_dropd, whisper_language, device_dropd], [whisper_model_dropd, whisper_language, device_dropd, audio])
|
||||
whisper_language.change(lambda x: params.update({"whipser_language": x}), whisper_language, None)
|
||||
auto_submit.change(lambda x: params.update({"auto_submit": x}), auto_submit, None)
|
||||
|
||||
|
||||
def custom_js():
|
||||
"""
|
||||
Returns custom javascript as a string. It is applied whenever the web UI is
|
||||
loaded.
|
||||
:return:
|
||||
"""
|
||||
with open(Path(__file__).parent.resolve() / "script.js", "r") as f:
|
||||
return f.read()
|
||||
|
||||
116
js/main.js
116
js/main.js
@ -7,30 +7,30 @@ main_parent.parentNode.style = "gap: 0";
|
||||
main_parent.parentNode.parentNode.style = "padding: 0";
|
||||
|
||||
document.querySelector(".header_bar").addEventListener("click", function(event) {
|
||||
if (event.target.tagName === "BUTTON") {
|
||||
if (event.target.tagName !== "BUTTON") return;
|
||||
|
||||
const buttonText = event.target.textContent.trim();
|
||||
const extensionsVisible = ["Chat", "Default", "Notebook"].includes(buttonText);
|
||||
const chatVisible = buttonText === "Chat";
|
||||
const showControlsChecked = document.querySelector("#show-controls input").checked;
|
||||
const extensions = document.querySelector("#extensions");
|
||||
|
||||
let chat_visible = (buttonText == "Chat");
|
||||
let default_visible = (buttonText == "Default");
|
||||
let notebook_visible = (buttonText == "Notebook");
|
||||
if (extensionsVisible) {
|
||||
if (extensions) {
|
||||
extensions.style.display = "flex";
|
||||
extensions.style.maxWidth = chatVisible ? "880px" : "none";
|
||||
extensions.style.padding = chatVisible ? "0px" : "15px";
|
||||
}
|
||||
this.style.marginBottom = chatVisible ? "0px" : "19px";
|
||||
|
||||
// Check if one of the generation tabs is visible
|
||||
if (chat_visible || notebook_visible || default_visible) {
|
||||
extensions && (extensions.style.display = "flex");
|
||||
|
||||
if (chat_visible) {
|
||||
this.style.marginBottom = "0px";
|
||||
extensions && (extensions.style.maxWidth = "880px");
|
||||
extensions && (extensions.style.padding = "0px");
|
||||
} else {
|
||||
this.style.marginBottom = "19px";
|
||||
extensions && (extensions.style.maxWidth = "none");
|
||||
extensions && (extensions.style.padding = "15px");
|
||||
if (chatVisible && !showControlsChecked) {
|
||||
document.querySelectorAll("#chat-tab > div > :nth-child(n+2), #extensions").forEach(element => {
|
||||
element.style.display = "none";
|
||||
});
|
||||
}
|
||||
} else {
|
||||
this.style.marginBottom = "19px";
|
||||
extensions && (extensions.style.display = "none");
|
||||
}
|
||||
if (extensions) extensions.style.display = "none";
|
||||
}
|
||||
});
|
||||
|
||||
@ -98,20 +98,6 @@ document.addEventListener("keydown", function(event) {
|
||||
document.getElementById("Impersonate").click();
|
||||
}
|
||||
|
||||
// Switch between tabs on Tab
|
||||
else if (!event.ctrlKey && !event.shiftKey && !event.altKey && !event.metaKey && event.key === "Tab") {
|
||||
event.preventDefault();
|
||||
var parametersButton = document.getElementById("parameters-button");
|
||||
var parentContainer = parametersButton.parentNode;
|
||||
var selectedChild = parentContainer.querySelector(".selected");
|
||||
|
||||
if (selectedChild.id == "parameters-button") {
|
||||
document.getElementById(previousTabId).click();
|
||||
} else {
|
||||
previousTabId = selectedChild.id;
|
||||
parametersButton.click();
|
||||
}
|
||||
}
|
||||
});
|
||||
|
||||
//------------------------------------------------
|
||||
@ -548,3 +534,69 @@ document.querySelectorAll(".focus-on-chat-input").forEach(element => {
|
||||
document.querySelector("#chat-input textarea").focus();
|
||||
});
|
||||
});
|
||||
|
||||
//------------------------------------------------
|
||||
// Fix a border around the "past chats" menu
|
||||
//------------------------------------------------
|
||||
document.getElementById("past-chats").parentNode.style.borderRadius = "0px";
|
||||
|
||||
//------------------------------------------------
|
||||
// Allow the character dropdown to coexist at the
|
||||
// Chat tab and the Parameters > Character tab
|
||||
//------------------------------------------------
|
||||
|
||||
const headerBar = document.querySelector(".header_bar");
|
||||
let originalParent;
|
||||
let originalIndex; // To keep track of the original position
|
||||
let movedElement;
|
||||
|
||||
function moveToChatTab() {
|
||||
const characterMenu = document.getElementById("character-menu");
|
||||
const grandParent = characterMenu.parentElement.parentElement;
|
||||
|
||||
// Save the initial location for the character dropdown
|
||||
if (!originalParent) {
|
||||
originalParent = grandParent.parentElement;
|
||||
originalIndex = Array.from(originalParent.children).indexOf(grandParent);
|
||||
movedElement = grandParent;
|
||||
}
|
||||
|
||||
// Do not show the Character dropdown in the Chat tab when "instruct" mode is selected
|
||||
const instructRadio = document.querySelector("#chat-mode input[value=\"instruct\"]");
|
||||
if (instructRadio && instructRadio.checked) {
|
||||
grandParent.style.display = "none";
|
||||
}
|
||||
|
||||
const chatControlsFirstChild = document.querySelector("#chat-controls").firstElementChild;
|
||||
const newParent = chatControlsFirstChild;
|
||||
let newPosition = newParent.children.length - 2;
|
||||
|
||||
newParent.insertBefore(grandParent, newParent.children[newPosition]);
|
||||
document.getElementById("save-character").style.display = "none";
|
||||
}
|
||||
|
||||
function restoreOriginalPosition() {
|
||||
if (originalParent && movedElement) {
|
||||
if (originalIndex >= originalParent.children.length) {
|
||||
originalParent.appendChild(movedElement);
|
||||
} else {
|
||||
originalParent.insertBefore(movedElement, originalParent.children[originalIndex]);
|
||||
}
|
||||
|
||||
document.getElementById("save-character").style.display = "";
|
||||
movedElement.style.display = "";
|
||||
}
|
||||
}
|
||||
|
||||
headerBar.addEventListener("click", (e) => {
|
||||
if (e.target.tagName === "BUTTON") {
|
||||
const tabName = e.target.textContent.trim();
|
||||
if (tabName === "Chat") {
|
||||
moveToChatTab();
|
||||
} else {
|
||||
restoreOriginalPosition();
|
||||
}
|
||||
}
|
||||
});
|
||||
|
||||
moveToChatTab();
|
||||
|
||||
@ -73,7 +73,7 @@ def add_lora_autogptq(lora_names):
|
||||
if len(lora_names) > 1:
|
||||
logger.warning('AutoGPTQ can only work with 1 LoRA at the moment. Only the first one in the list will be loaded.')
|
||||
if not shared.args.no_inject_fused_attention:
|
||||
logger.warning('Fused Atttention + AutoGPTQ may break Lora loading. Disable it.')
|
||||
logger.warning('Fused Attention + AutoGPTQ may break Lora loading. Disable it.')
|
||||
|
||||
peft_config = GPTQLoraConfig(
|
||||
inference_mode=True,
|
||||
|
||||
@ -1,18 +0,0 @@
|
||||
def get_alpha_value(alpha, base):
|
||||
'''
|
||||
Gets alpha_value from alpha_value and rope_freq_base
|
||||
'''
|
||||
if base > 0:
|
||||
return (base / 10000.) ** (63 / 64.)
|
||||
else:
|
||||
return alpha
|
||||
|
||||
|
||||
def get_rope_freq_base(alpha, base):
|
||||
'''
|
||||
Gets rope_freq_base from alpha_value and rope_freq_base
|
||||
'''
|
||||
if base > 0:
|
||||
return base
|
||||
else:
|
||||
return 10000 * alpha ** (64 / 63.)
|
||||
@ -43,19 +43,27 @@ def my_open(*args, **kwargs):
|
||||
with original_open(*args, **kwargs) as f:
|
||||
file_contents = f.read()
|
||||
|
||||
file_contents = file_contents.replace(b'\t\t<script\n\t\t\tsrc="https://cdnjs.cloudflare.com/ajax/libs/iframe-resizer/4.3.9/iframeResizer.contentWindow.min.js"\n\t\t\tasync\n\t\t></script>', b'')
|
||||
file_contents = file_contents.replace(b'cdnjs.cloudflare.com', b'127.0.0.1')
|
||||
if len(args) > 1 and args[1] == 'rb':
|
||||
file_contents = file_contents.decode('utf-8')
|
||||
|
||||
file_contents = file_contents.replace('\t\t<script\n\t\t\tsrc="https://cdnjs.cloudflare.com/ajax/libs/iframe-resizer/4.3.9/iframeResizer.contentWindow.min.js"\n\t\t\tasync\n\t\t></script>', '')
|
||||
file_contents = file_contents.replace('cdnjs.cloudflare.com', '127.0.0.1')
|
||||
file_contents = file_contents.replace(
|
||||
b'</head>',
|
||||
b'\n <script src="file/js/katex/katex.min.js"></script>'
|
||||
b'\n <script src="file/js/katex/auto-render.min.js"></script>'
|
||||
b'\n <script src="file/js/highlightjs/highlight.min.js"></script>'
|
||||
b'\n <script src="file/js/highlightjs/highlightjs-copy.min.js"></script>'
|
||||
b'\n <script>hljs.addPlugin(new CopyButtonPlugin());</script>'
|
||||
b'\n </head>'
|
||||
'</head>',
|
||||
'\n <script src="file/js/katex/katex.min.js"></script>'
|
||||
'\n <script src="file/js/katex/auto-render.min.js"></script>'
|
||||
'\n <script src="file/js/highlightjs/highlight.min.js"></script>'
|
||||
'\n <script src="file/js/highlightjs/highlightjs-copy.min.js"></script>'
|
||||
'\n <script>hljs.addPlugin(new CopyButtonPlugin());</script>'
|
||||
'\n </head>'
|
||||
)
|
||||
|
||||
if len(args) > 1 and args[1] == 'rb':
|
||||
file_contents = file_contents.encode('utf-8')
|
||||
return io.BytesIO(file_contents)
|
||||
else:
|
||||
return io.StringIO(file_contents)
|
||||
|
||||
else:
|
||||
return original_open(*args, **kwargs)
|
||||
|
||||
|
||||
@ -3,6 +3,7 @@ import copy
|
||||
import functools
|
||||
import html
|
||||
import json
|
||||
import pprint
|
||||
import re
|
||||
from datetime import datetime
|
||||
from functools import partial
|
||||
@ -259,10 +260,27 @@ def get_stopping_strings(state):
|
||||
suffix_bot + prefix_user,
|
||||
]
|
||||
|
||||
# Try to find the EOT token
|
||||
for item in stopping_strings.copy():
|
||||
item = item.strip()
|
||||
if item.startswith("<") and ">" in item:
|
||||
stopping_strings.append(item.split(">")[0] + ">")
|
||||
elif item.startswith("[") and "]" in item:
|
||||
stopping_strings.append(item.split("]")[0] + "]")
|
||||
|
||||
if 'stopping_strings' in state and isinstance(state['stopping_strings'], list):
|
||||
stopping_strings += state.pop('stopping_strings')
|
||||
|
||||
return list(set(stopping_strings))
|
||||
# Remove redundant items that start with another item
|
||||
result = [item for item in stopping_strings if not any(item.startswith(other) and item != other for other in stopping_strings)]
|
||||
result = list(set(result))
|
||||
|
||||
if shared.args.verbose:
|
||||
logger.info("STOPPING_STRINGS=")
|
||||
pprint.PrettyPrinter(indent=4, sort_dicts=False).pprint(result)
|
||||
print()
|
||||
|
||||
return result
|
||||
|
||||
|
||||
def chatbot_wrapper(text, state, regenerate=False, _continue=False, loading_message=True, for_ui=False):
|
||||
@ -492,7 +510,7 @@ def save_history(history, unique_id, character, mode):
|
||||
p.parent.mkdir(parents=True)
|
||||
|
||||
with open(p, 'w', encoding='utf-8') as f:
|
||||
f.write(json.dumps(history, indent=4))
|
||||
f.write(json.dumps(history, indent=4, ensure_ascii=False))
|
||||
|
||||
|
||||
def rename_history(old_id, new_id, character, mode):
|
||||
@ -505,17 +523,16 @@ def rename_history(old_id, new_id, character, mode):
|
||||
logger.error(f"The following path is not allowed: \"{new_p}\".")
|
||||
elif new_p == old_p:
|
||||
logger.info("The provided path is identical to the old one.")
|
||||
elif new_p.exists():
|
||||
logger.error(f"The new path already exists and will not be overwritten: \"{new_p}\".")
|
||||
else:
|
||||
logger.info(f"Renaming \"{old_p}\" to \"{new_p}\"")
|
||||
old_p.rename(new_p)
|
||||
|
||||
|
||||
def find_all_histories(state):
|
||||
if shared.args.multi_user:
|
||||
return ['']
|
||||
|
||||
def get_paths(state):
|
||||
if state['mode'] == 'instruct':
|
||||
paths = Path('logs/instruct').glob('*.json')
|
||||
return Path('logs/instruct').glob('*.json')
|
||||
else:
|
||||
character = state['character_menu']
|
||||
|
||||
@ -533,12 +550,55 @@ def find_all_histories(state):
|
||||
p.parent.mkdir(exist_ok=True)
|
||||
new_p.rename(p)
|
||||
|
||||
paths = Path(f'logs/chat/{character}').glob('*.json')
|
||||
return Path(f'logs/chat/{character}').glob('*.json')
|
||||
|
||||
|
||||
def find_all_histories(state):
|
||||
if shared.args.multi_user:
|
||||
return ['']
|
||||
|
||||
paths = get_paths(state)
|
||||
histories = sorted(paths, key=lambda x: x.stat().st_mtime, reverse=True)
|
||||
histories = [path.stem for path in histories]
|
||||
return [path.stem for path in histories]
|
||||
|
||||
return histories
|
||||
|
||||
def find_all_histories_with_first_prompts(state):
|
||||
if shared.args.multi_user:
|
||||
return []
|
||||
|
||||
paths = get_paths(state)
|
||||
histories = sorted(paths, key=lambda x: x.stat().st_mtime, reverse=True)
|
||||
|
||||
result = []
|
||||
for i, path in enumerate(histories):
|
||||
filename = path.stem
|
||||
if re.match(r'^[0-9]{8}-[0-9]{2}-[0-9]{2}-[0-9]{2}$', filename):
|
||||
with open(path, 'r', encoding='utf-8') as f:
|
||||
data = json.load(f)
|
||||
|
||||
first_prompt = ""
|
||||
if data and 'visible' in data and len(data['visible']) > 0:
|
||||
if data['internal'][0][0] == '<|BEGIN-VISIBLE-CHAT|>':
|
||||
if len(data['visible']) > 1:
|
||||
first_prompt = html.unescape(data['visible'][1][0])
|
||||
elif i == 0:
|
||||
first_prompt = "New chat"
|
||||
else:
|
||||
first_prompt = html.unescape(data['visible'][0][0])
|
||||
elif i == 0:
|
||||
first_prompt = "New chat"
|
||||
else:
|
||||
first_prompt = filename
|
||||
|
||||
first_prompt = first_prompt.strip()
|
||||
|
||||
# Truncate the first prompt if it's longer than 32 characters
|
||||
if len(first_prompt) > 32:
|
||||
first_prompt = first_prompt[:29] + '...'
|
||||
|
||||
result.append((first_prompt, filename))
|
||||
|
||||
return result
|
||||
|
||||
|
||||
def load_latest_history(state):
|
||||
@ -569,17 +629,17 @@ def load_history_after_deletion(state, idx):
|
||||
if shared.args.multi_user:
|
||||
return start_new_chat(state)
|
||||
|
||||
histories = find_all_histories(state)
|
||||
histories = find_all_histories_with_first_prompts(state)
|
||||
idx = min(int(idx), len(histories) - 1)
|
||||
idx = max(0, idx)
|
||||
|
||||
if len(histories) > 0:
|
||||
history = load_history(histories[idx], state['character_menu'], state['mode'])
|
||||
history = load_history(histories[idx][1], state['character_menu'], state['mode'])
|
||||
else:
|
||||
history = start_new_chat(state)
|
||||
histories = find_all_histories(state)
|
||||
histories = find_all_histories_with_first_prompts(state)
|
||||
|
||||
return history, gr.update(choices=histories, value=histories[idx])
|
||||
return history, gr.update(choices=histories, value=histories[idx][1])
|
||||
|
||||
|
||||
def update_character_menu_after_deletion(idx):
|
||||
|
||||
@ -48,6 +48,8 @@ class Exllamav2Model:
|
||||
config.scale_pos_emb = shared.args.compress_pos_emb
|
||||
config.scale_alpha_value = shared.args.alpha_value
|
||||
config.no_flash_attn = shared.args.no_flash_attn
|
||||
config.no_xformers = shared.args.no_xformers
|
||||
config.no_sdpa = shared.args.no_sdpa
|
||||
config.num_experts_per_token = int(shared.args.num_experts_per_token)
|
||||
|
||||
model = ExLlamaV2(config)
|
||||
|
||||
@ -176,6 +176,8 @@ class Exllamav2HF(PreTrainedModel):
|
||||
config.scale_pos_emb = shared.args.compress_pos_emb
|
||||
config.scale_alpha_value = shared.args.alpha_value
|
||||
config.no_flash_attn = shared.args.no_flash_attn
|
||||
config.no_xformers = shared.args.no_xformers
|
||||
config.no_sdpa = shared.args.no_sdpa
|
||||
config.num_experts_per_token = int(shared.args.num_experts_per_token)
|
||||
|
||||
return Exllamav2HF(config)
|
||||
|
||||
@ -32,7 +32,7 @@ def clone_or_pull_repository(github_url):
|
||||
yield f"Cloning {github_url}..."
|
||||
clone_output = subprocess.check_output(["git", "clone", github_url, repo_path], stderr=subprocess.STDOUT)
|
||||
new_extensions.add(repo_name)
|
||||
yield f"The extension `{repo_name}` has been downloaded.\n\nPlease close the the web UI completely and launch it again to be able to load it."
|
||||
yield f"The extension `{repo_name}` has been downloaded.\n\nPlease close the web UI completely and launch it again to be able to load it."
|
||||
return clone_output.decode()
|
||||
except subprocess.CalledProcessError as e:
|
||||
return str(e)
|
||||
|
||||
@ -85,15 +85,20 @@ def convert_to_markdown(string):
|
||||
|
||||
# Unfinished list, like "\n1.". A |delete| string is added and then
|
||||
# removed to force a <ol> or <ul> to be generated instead of a <p>.
|
||||
if re.search(r'(\n\d+\.?|\n\*\s*)$', result):
|
||||
list_item_pattern = r'(\n\d+\.?|\n\s*[-*+]\s*([*_~]{1,3})?)$'
|
||||
if re.search(list_item_pattern, result):
|
||||
delete_str = '|delete|'
|
||||
|
||||
if re.search(r'(\d+\.?)$', result) and not result.endswith('.'):
|
||||
result += '.'
|
||||
|
||||
result = re.sub(r'(\n\d+\.?|\n\*\s*)$', r'\g<1> ' + delete_str, result)
|
||||
# Add the delete string after the list item
|
||||
result = re.sub(list_item_pattern, r'\g<1> ' + delete_str, result)
|
||||
|
||||
# Convert to HTML using markdown
|
||||
html_output = markdown.markdown(result, extensions=['fenced_code', 'tables'])
|
||||
|
||||
# Remove the delete string from the HTML output
|
||||
pos = html_output.rfind(delete_str)
|
||||
if pos > -1:
|
||||
html_output = html_output[:pos] + html_output[pos + len(delete_str):]
|
||||
|
||||
@ -1,3 +1,5 @@
|
||||
import importlib
|
||||
import platform
|
||||
from typing import Sequence
|
||||
|
||||
from tqdm import tqdm
|
||||
@ -5,20 +7,46 @@ from tqdm import tqdm
|
||||
from modules import shared
|
||||
from modules.cache_utils import process_llamacpp_cache
|
||||
|
||||
try:
|
||||
import llama_cpp
|
||||
except:
|
||||
llama_cpp = None
|
||||
|
||||
imported_module = None
|
||||
|
||||
|
||||
def llama_cpp_lib():
|
||||
global imported_module
|
||||
|
||||
# Determine the platform
|
||||
is_macos = platform.system() == 'Darwin'
|
||||
|
||||
# Define the library names based on the platform
|
||||
if is_macos:
|
||||
lib_names = [
|
||||
(None, 'llama_cpp')
|
||||
]
|
||||
else:
|
||||
lib_names = [
|
||||
('cpu', 'llama_cpp'),
|
||||
('tensorcores', 'llama_cpp_cuda_tensorcores'),
|
||||
(None, 'llama_cpp_cuda'),
|
||||
(None, 'llama_cpp')
|
||||
]
|
||||
|
||||
for arg, lib_name in lib_names:
|
||||
should_import = (arg is None or getattr(shared.args, arg))
|
||||
|
||||
if should_import:
|
||||
if imported_module and imported_module != lib_name:
|
||||
# Conflict detected, raise an exception
|
||||
raise Exception(f"Cannot import `{lib_name}` because `{imported_module}` is already imported. Switching to a different version of llama-cpp-python currently requires a server restart.")
|
||||
|
||||
try:
|
||||
import llama_cpp_cuda
|
||||
except:
|
||||
llama_cpp_cuda = None
|
||||
return_lib = importlib.import_module(lib_name)
|
||||
imported_module = lib_name
|
||||
monkey_patch_llama_cpp_python(return_lib)
|
||||
return return_lib
|
||||
except ImportError:
|
||||
continue
|
||||
|
||||
try:
|
||||
import llama_cpp_cuda_tensorcores
|
||||
except:
|
||||
llama_cpp_cuda_tensorcores = None
|
||||
return None
|
||||
|
||||
|
||||
def eval_with_progress(self, tokens: Sequence[int]):
|
||||
@ -63,10 +91,12 @@ def eval_with_progress(self, tokens: Sequence[int]):
|
||||
self.n_tokens += n_tokens
|
||||
|
||||
|
||||
def monkey_patch_generate(lib):
|
||||
def monkey_patch_llama_cpp_python(lib):
|
||||
if getattr(lib.Llama, '_is_patched', False):
|
||||
# If the patch is already applied, do nothing
|
||||
return
|
||||
|
||||
def my_generate(self, *args, **kwargs):
|
||||
|
||||
if shared.args.streaming_llm:
|
||||
new_sequence = args[0]
|
||||
past_sequence = self._input_ids
|
||||
@ -77,11 +107,9 @@ def monkey_patch_generate(lib):
|
||||
for output in self.original_generate(*args, **kwargs):
|
||||
yield output
|
||||
|
||||
lib.Llama.eval = eval_with_progress
|
||||
lib.Llama.original_generate = lib.Llama.generate
|
||||
lib.Llama.generate = my_generate
|
||||
|
||||
|
||||
for lib in [llama_cpp, llama_cpp_cuda, llama_cpp_cuda_tensorcores]:
|
||||
if lib is not None:
|
||||
lib.Llama.eval = eval_with_progress
|
||||
monkey_patch_generate(lib)
|
||||
# Set the flag to indicate that the patch has been applied
|
||||
lib.Llama._is_patched = True
|
||||
|
||||
@ -7,35 +7,10 @@ from torch.nn import CrossEntropyLoss
|
||||
from transformers import GenerationConfig, PretrainedConfig, PreTrainedModel
|
||||
from transformers.modeling_outputs import CausalLMOutputWithPast
|
||||
|
||||
from modules import RoPE, llama_cpp_python_hijack, shared
|
||||
from modules import shared
|
||||
from modules.llama_cpp_python_hijack import llama_cpp_lib
|
||||
from modules.logging_colors import logger
|
||||
|
||||
try:
|
||||
import llama_cpp
|
||||
except:
|
||||
llama_cpp = None
|
||||
|
||||
try:
|
||||
import llama_cpp_cuda
|
||||
except:
|
||||
llama_cpp_cuda = None
|
||||
|
||||
try:
|
||||
import llama_cpp_cuda_tensorcores
|
||||
except:
|
||||
llama_cpp_cuda_tensorcores = None
|
||||
|
||||
|
||||
def llama_cpp_lib():
|
||||
if shared.args.cpu and llama_cpp is not None:
|
||||
return llama_cpp
|
||||
elif shared.args.tensorcores and llama_cpp_cuda_tensorcores is not None:
|
||||
return llama_cpp_cuda_tensorcores
|
||||
elif llama_cpp_cuda is not None:
|
||||
return llama_cpp_cuda
|
||||
else:
|
||||
return llama_cpp
|
||||
|
||||
|
||||
class LlamacppHF(PreTrainedModel):
|
||||
def __init__(self, model, path):
|
||||
@ -212,7 +187,7 @@ class LlamacppHF(PreTrainedModel):
|
||||
'mul_mat_q': not shared.args.no_mul_mat_q,
|
||||
'numa': shared.args.numa,
|
||||
'n_gpu_layers': shared.args.n_gpu_layers,
|
||||
'rope_freq_base': RoPE.get_rope_freq_base(shared.args.alpha_value, shared.args.rope_freq_base),
|
||||
'rope_freq_base': shared.args.rope_freq_base,
|
||||
'tensor_split': tensor_split_list,
|
||||
'rope_freq_scale': 1.0 / shared.args.compress_pos_emb,
|
||||
'logits_all': shared.args.logits_all,
|
||||
@ -221,6 +196,13 @@ class LlamacppHF(PreTrainedModel):
|
||||
'flash_attn': shared.args.flash_attn
|
||||
}
|
||||
|
||||
if shared.args.cache_4bit:
|
||||
params["type_k"] = 2
|
||||
params["type_v"] = 2
|
||||
elif shared.args.cache_8bit:
|
||||
params["type_k"] = 8
|
||||
params["type_v"] = 8
|
||||
|
||||
Llama = llama_cpp_lib().Llama
|
||||
model = Llama(**params)
|
||||
|
||||
|
||||
@ -4,37 +4,12 @@ from functools import partial
|
||||
import numpy as np
|
||||
import torch
|
||||
|
||||
from modules import RoPE, llama_cpp_python_hijack, shared
|
||||
from modules import shared
|
||||
from modules.callbacks import Iteratorize
|
||||
from modules.llama_cpp_python_hijack import llama_cpp_lib
|
||||
from modules.logging_colors import logger
|
||||
from modules.text_generation import get_max_prompt_length
|
||||
|
||||
try:
|
||||
import llama_cpp
|
||||
except:
|
||||
llama_cpp = None
|
||||
|
||||
try:
|
||||
import llama_cpp_cuda
|
||||
except:
|
||||
llama_cpp_cuda = None
|
||||
|
||||
try:
|
||||
import llama_cpp_cuda_tensorcores
|
||||
except:
|
||||
llama_cpp_cuda_tensorcores = None
|
||||
|
||||
|
||||
def llama_cpp_lib():
|
||||
if shared.args.cpu and llama_cpp is not None:
|
||||
return llama_cpp
|
||||
elif shared.args.tensorcores and llama_cpp_cuda_tensorcores is not None:
|
||||
return llama_cpp_cuda_tensorcores
|
||||
elif llama_cpp_cuda is not None:
|
||||
return llama_cpp_cuda
|
||||
else:
|
||||
return llama_cpp
|
||||
|
||||
|
||||
def ban_eos_logits_processor(eos_token, input_ids, logits):
|
||||
logits[eos_token] = -float('inf')
|
||||
@ -92,7 +67,7 @@ class LlamaCppModel:
|
||||
'mul_mat_q': not shared.args.no_mul_mat_q,
|
||||
'numa': shared.args.numa,
|
||||
'n_gpu_layers': shared.args.n_gpu_layers,
|
||||
'rope_freq_base': RoPE.get_rope_freq_base(shared.args.alpha_value, shared.args.rope_freq_base),
|
||||
'rope_freq_base': shared.args.rope_freq_base,
|
||||
'tensor_split': tensor_split_list,
|
||||
'rope_freq_scale': 1.0 / shared.args.compress_pos_emb,
|
||||
'offload_kqv': not shared.args.no_offload_kqv,
|
||||
@ -100,6 +75,13 @@ class LlamaCppModel:
|
||||
'flash_attn': shared.args.flash_attn
|
||||
}
|
||||
|
||||
if shared.args.cache_4bit:
|
||||
params["type_k"] = 2
|
||||
params["type_v"] = 2
|
||||
elif shared.args.cache_8bit:
|
||||
params["type_k"] = 8
|
||||
params["type_v"] = 8
|
||||
|
||||
result.model = Llama(**params)
|
||||
if cache_capacity > 0:
|
||||
result.model.set_cache(LlamaCache(capacity_bytes=cache_capacity))
|
||||
|
||||
@ -21,8 +21,8 @@ loaders_and_params = OrderedDict({
|
||||
'trust_remote_code',
|
||||
'no_use_fast',
|
||||
'use_flash_attention_2',
|
||||
'use_eager_attention',
|
||||
'alpha_value',
|
||||
'rope_freq_base',
|
||||
'compress_pos_emb',
|
||||
'disable_exllama',
|
||||
'disable_exllamav2',
|
||||
@ -31,6 +31,8 @@ loaders_and_params = OrderedDict({
|
||||
'llama.cpp': [
|
||||
'n_ctx',
|
||||
'n_gpu_layers',
|
||||
'cache_8bit',
|
||||
'cache_4bit',
|
||||
'tensor_split',
|
||||
'n_batch',
|
||||
'threads',
|
||||
@ -38,7 +40,6 @@ loaders_and_params = OrderedDict({
|
||||
'no_mmap',
|
||||
'mlock',
|
||||
'no_mul_mat_q',
|
||||
'alpha_value',
|
||||
'rope_freq_base',
|
||||
'compress_pos_emb',
|
||||
'cpu',
|
||||
@ -46,13 +47,15 @@ loaders_and_params = OrderedDict({
|
||||
'no_offload_kqv',
|
||||
'row_split',
|
||||
'tensorcores',
|
||||
'flash-attn',
|
||||
'flash_attn',
|
||||
'streaming_llm',
|
||||
'attention_sink_size',
|
||||
],
|
||||
'llamacpp_HF': [
|
||||
'n_ctx',
|
||||
'n_gpu_layers',
|
||||
'cache_8bit',
|
||||
'cache_4bit',
|
||||
'tensor_split',
|
||||
'n_batch',
|
||||
'threads',
|
||||
@ -60,7 +63,6 @@ loaders_and_params = OrderedDict({
|
||||
'no_mmap',
|
||||
'mlock',
|
||||
'no_mul_mat_q',
|
||||
'alpha_value',
|
||||
'rope_freq_base',
|
||||
'compress_pos_emb',
|
||||
'cpu',
|
||||
@ -72,7 +74,7 @@ loaders_and_params = OrderedDict({
|
||||
'no_offload_kqv',
|
||||
'row_split',
|
||||
'tensorcores',
|
||||
'flash-attn',
|
||||
'flash_attn',
|
||||
'streaming_llm',
|
||||
'attention_sink_size',
|
||||
'llamacpp_HF_info',
|
||||
@ -82,6 +84,8 @@ loaders_and_params = OrderedDict({
|
||||
'max_seq_len',
|
||||
'cfg_cache',
|
||||
'no_flash_attn',
|
||||
'no_xformers',
|
||||
'no_sdpa',
|
||||
'num_experts_per_token',
|
||||
'cache_8bit',
|
||||
'cache_4bit',
|
||||
@ -95,6 +99,8 @@ loaders_and_params = OrderedDict({
|
||||
'gpu_split',
|
||||
'max_seq_len',
|
||||
'no_flash_attn',
|
||||
'no_xformers',
|
||||
'no_sdpa',
|
||||
'num_experts_per_token',
|
||||
'cache_8bit',
|
||||
'cache_4bit',
|
||||
@ -134,6 +140,11 @@ loaders_and_params = OrderedDict({
|
||||
'hqq_backend',
|
||||
'trust_remote_code',
|
||||
'no_use_fast',
|
||||
],
|
||||
'TensorRT-LLM': [
|
||||
'max_seq_len',
|
||||
'cpp_runner',
|
||||
'tensorrt_llm_info',
|
||||
]
|
||||
})
|
||||
|
||||
@ -319,6 +330,16 @@ loaders_samplers = {
|
||||
'skip_special_tokens',
|
||||
'auto_max_new_tokens',
|
||||
},
|
||||
'TensorRT-LLM': {
|
||||
'temperature',
|
||||
'top_p',
|
||||
'top_k',
|
||||
'repetition_penalty',
|
||||
'presence_penalty',
|
||||
'frequency_penalty',
|
||||
'ban_eos_token',
|
||||
'auto_max_new_tokens',
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
|
||||
@ -16,15 +16,20 @@ def get_next_logits(*args, **kwargs):
|
||||
if shared.args.idle_timeout > 0 and shared.model is None and shared.previous_model_name not in [None, 'None']:
|
||||
shared.model, shared.tokenizer = load_model(shared.previous_model_name)
|
||||
|
||||
needs_lock = not args[2] # use_samplers
|
||||
if needs_lock:
|
||||
shared.generation_lock.acquire()
|
||||
|
||||
try:
|
||||
result = _get_next_logits(*args, **kwargs)
|
||||
except Exception:
|
||||
traceback.print_exc()
|
||||
result = None
|
||||
|
||||
if needs_lock:
|
||||
models.last_generation_time = time.time()
|
||||
shared.generation_lock.release()
|
||||
|
||||
return result
|
||||
|
||||
|
||||
|
||||
@ -1,5 +1,4 @@
|
||||
import gc
|
||||
import logging
|
||||
import os
|
||||
import pprint
|
||||
import re
|
||||
@ -26,10 +25,9 @@ from transformers import (
|
||||
)
|
||||
|
||||
import modules.shared as shared
|
||||
from modules import RoPE, sampler_hijack
|
||||
from modules import sampler_hijack
|
||||
from modules.logging_colors import logger
|
||||
from modules.models_settings import get_model_metadata
|
||||
from modules.relative_imports import RelativeImport
|
||||
|
||||
transformers.logging.set_verbosity_error()
|
||||
|
||||
@ -79,6 +77,7 @@ def load_model(model_name, loader=None):
|
||||
'ExLlamav2_HF': ExLlamav2_HF_loader,
|
||||
'AutoAWQ': AutoAWQ_loader,
|
||||
'HQQ': HQQ_loader,
|
||||
'TensorRT-LLM': TensorRT_LLM_loader,
|
||||
}
|
||||
|
||||
metadata = get_model_metadata(model_name)
|
||||
@ -103,7 +102,7 @@ def load_model(model_name, loader=None):
|
||||
tokenizer = load_tokenizer(model_name, model)
|
||||
|
||||
shared.settings.update({k: v for k, v in metadata.items() if k in shared.settings})
|
||||
if loader.lower().startswith('exllama'):
|
||||
if loader.lower().startswith('exllama') or loader.lower().startswith('tensorrt'):
|
||||
shared.settings['truncation_length'] = shared.args.max_seq_len
|
||||
elif loader in ['llama.cpp', 'llamacpp_HF']:
|
||||
shared.settings['truncation_length'] = shared.args.n_ctx
|
||||
@ -147,6 +146,9 @@ def huggingface_loader(model_name):
|
||||
if shared.args.force_safetensors:
|
||||
params['force_safetensors'] = True
|
||||
|
||||
if shared.args.use_eager_attention:
|
||||
params['attn_implementation'] = 'eager'
|
||||
|
||||
config = AutoConfig.from_pretrained(path_to_model, trust_remote_code=shared.args.trust_remote_code)
|
||||
|
||||
if 'chatglm' in model_name.lower():
|
||||
@ -250,7 +252,7 @@ def huggingface_loader(model_name):
|
||||
if shared.args.compress_pos_emb > 1:
|
||||
params['rope_scaling'] = {'type': 'linear', 'factor': shared.args.compress_pos_emb}
|
||||
elif shared.args.alpha_value > 1:
|
||||
params['rope_scaling'] = {'type': 'dynamic', 'factor': RoPE.get_alpha_value(shared.args.alpha_value, shared.args.rope_freq_base)}
|
||||
params['rope_scaling'] = {'type': 'dynamic', 'factor': shared.args.alpha_value}
|
||||
|
||||
logger.info("TRANSFORMERS_PARAMS=")
|
||||
pprint.PrettyPrinter(indent=4, sort_dicts=False).pprint(params)
|
||||
@ -339,6 +341,13 @@ def HQQ_loader(model_name):
|
||||
return model
|
||||
|
||||
|
||||
def TensorRT_LLM_loader(model_name):
|
||||
from modules.tensorrt_llm import TensorRTLLMModel
|
||||
|
||||
model = TensorRTLLMModel.from_pretrained(model_name)
|
||||
return model
|
||||
|
||||
|
||||
def get_max_memory_dict():
|
||||
max_memory = {}
|
||||
max_cpu_memory = shared.args.cpu_memory.strip() if shared.args.cpu_memory is not None else '99GiB'
|
||||
|
||||
@ -9,6 +9,8 @@ from modules import chat, loaders, metadata_gguf, shared, ui
|
||||
|
||||
def get_fallback_settings():
|
||||
return {
|
||||
'bf16': False,
|
||||
'use_eager_attention': False,
|
||||
'wbits': 'None',
|
||||
'groupsize': 'None',
|
||||
'desc_act': False,
|
||||
@ -16,6 +18,7 @@ def get_fallback_settings():
|
||||
'n_ctx': 2048,
|
||||
'rope_freq_base': 0,
|
||||
'compress_pos_emb': 1,
|
||||
'alpha_value': 1,
|
||||
'truncation_length': shared.settings['truncation_length'],
|
||||
'skip_special_tokens': shared.settings['skip_special_tokens'],
|
||||
'custom_stopping_strings': shared.settings['custom_stopping_strings'],
|
||||
@ -58,13 +61,19 @@ def get_model_metadata(model):
|
||||
model_settings['rope_freq_base'] = metadata[k]
|
||||
elif k.endswith('rope.scale_linear'):
|
||||
model_settings['compress_pos_emb'] = metadata[k]
|
||||
elif k.endswith('rope.scaling.factor'):
|
||||
model_settings['compress_pos_emb'] = metadata[k]
|
||||
elif k.endswith('block_count'):
|
||||
model_settings['n_gpu_layers'] = metadata[k] + 1
|
||||
|
||||
if 'tokenizer.chat_template' in metadata:
|
||||
template = metadata['tokenizer.chat_template']
|
||||
eos_token = metadata['tokenizer.ggml.tokens'][metadata['tokenizer.ggml.eos_token_id']]
|
||||
if 'tokenizer.ggml.bos_token_id' in metadata:
|
||||
bos_token = metadata['tokenizer.ggml.tokens'][metadata['tokenizer.ggml.bos_token_id']]
|
||||
else:
|
||||
bos_token = ""
|
||||
|
||||
template = template.replace('eos_token', "'{}'".format(eos_token))
|
||||
template = template.replace('bos_token', "'{}'".format(bos_token))
|
||||
|
||||
@ -77,6 +86,9 @@ def get_model_metadata(model):
|
||||
# Transformers metadata
|
||||
if hf_metadata is not None:
|
||||
metadata = json.loads(open(path, 'r', encoding='utf-8').read())
|
||||
if 'pretrained_config' in metadata:
|
||||
metadata = metadata['pretrained_config']
|
||||
|
||||
for k in ['max_position_embeddings', 'model_max_length', 'max_seq_len']:
|
||||
if k in metadata:
|
||||
model_settings['truncation_length'] = metadata[k]
|
||||
@ -87,10 +99,18 @@ def get_model_metadata(model):
|
||||
elif 'attn_config' in metadata and 'rope_theta' in metadata['attn_config']:
|
||||
model_settings['rope_freq_base'] = metadata['attn_config']['rope_theta']
|
||||
|
||||
if 'rope_scaling' in metadata and type(metadata['rope_scaling']) is dict and all(key in metadata['rope_scaling'] for key in ('type', 'factor')):
|
||||
if 'rope_scaling' in metadata and isinstance(metadata['rope_scaling'], dict) and all(key in metadata['rope_scaling'] for key in ('type', 'factor')):
|
||||
if metadata['rope_scaling']['type'] == 'linear':
|
||||
model_settings['compress_pos_emb'] = metadata['rope_scaling']['factor']
|
||||
|
||||
# For Gemma-2
|
||||
if 'torch_dtype' in metadata and metadata['torch_dtype'] == 'bfloat16':
|
||||
model_settings['bf16'] = True
|
||||
|
||||
# For Gemma-2
|
||||
if 'architectures' in metadata and isinstance(metadata['architectures'], list) and 'Gemma2ForCausalLM' in metadata['architectures']:
|
||||
model_settings['use_eager_attention'] = True
|
||||
|
||||
# Read GPTQ metadata for old GPTQ loaders
|
||||
if 'quantization_config' in metadata and metadata['quantization_config'].get('quant_method', '') != 'exl2':
|
||||
if 'bits' in metadata['quantization_config']:
|
||||
@ -123,7 +143,7 @@ def get_model_metadata(model):
|
||||
for k in ['eos_token', 'bos_token']:
|
||||
if k in metadata:
|
||||
value = metadata[k]
|
||||
if type(value) is dict:
|
||||
if isinstance(value, dict):
|
||||
value = value['content']
|
||||
|
||||
template = template.replace(k, "'{}'".format(value))
|
||||
@ -158,7 +178,7 @@ def infer_loader(model_name, model_settings):
|
||||
path_to_model = Path(f'{shared.args.model_dir}/{model_name}')
|
||||
if not path_to_model.exists():
|
||||
loader = None
|
||||
elif (path_to_model / 'quantize_config.json').exists() or ('wbits' in model_settings and type(model_settings['wbits']) is int and model_settings['wbits'] > 0):
|
||||
elif (path_to_model / 'quantize_config.json').exists() or ('wbits' in model_settings and isinstance(model_settings['wbits'], int) and model_settings['wbits'] > 0):
|
||||
loader = 'ExLlamav2_HF'
|
||||
elif (path_to_model / 'quant_config.json').exists() or re.match(r'.*-awq', model_name.lower()):
|
||||
loader = 'AutoAWQ'
|
||||
@ -204,14 +224,11 @@ def update_model_parameters(state, initial=False):
|
||||
value = vars(shared.args_defaults)[element]
|
||||
|
||||
# Making some simple conversions
|
||||
if element in ['wbits', 'groupsize', 'pre_layer']:
|
||||
if element in ['wbits', 'groupsize']:
|
||||
value = int(value)
|
||||
elif element == 'cpu_memory' and value is not None:
|
||||
value = f"{value}MiB"
|
||||
|
||||
if element in ['pre_layer']:
|
||||
value = [value] if value > 0 else None
|
||||
|
||||
setattr(shared.args, element, value)
|
||||
|
||||
found_positive = False
|
||||
|
||||
@ -204,21 +204,25 @@ class DRYLogitsProcessor(LogitsProcessor):
|
||||
input_ids = input_ids[:, -self._range:]
|
||||
|
||||
for input_ids_row, scores_row in zip(input_ids, scores):
|
||||
# Raw integer must be extracted here to check for set membership.
|
||||
last_token = input_ids_row[-1].item()
|
||||
# Use normal Python data types for improved performance
|
||||
input_ids = input_ids_row.tolist()
|
||||
|
||||
last_token = input_ids[-1]
|
||||
if last_token in self.sequence_breakers:
|
||||
continue
|
||||
|
||||
# Exclude the last token as it always matches.
|
||||
match_indices = (input_ids_row[:-1] == last_token).nonzero()
|
||||
match_indices = []
|
||||
for idx, val in enumerate(input_ids[:-1]):
|
||||
if val == last_token:
|
||||
match_indices.append(idx)
|
||||
|
||||
# Stores the maximum matching sequence length
|
||||
# for each token immediately following the sequence in the input.
|
||||
match_lengths = {}
|
||||
|
||||
for i in match_indices:
|
||||
next_token = input_ids_row[i+1].item()
|
||||
next_token = input_ids[i + 1]
|
||||
|
||||
if next_token in self.sequence_breakers:
|
||||
continue
|
||||
@ -227,15 +231,15 @@ class DRYLogitsProcessor(LogitsProcessor):
|
||||
# so the match is at least of length 1.
|
||||
match_length = 1
|
||||
|
||||
# Extend the match backwards as far as possible.
|
||||
while True:
|
||||
# Extend the match backwards (at most to 50 to prevent exponent overflow at penalty calculation) (this cap also improves performance on worst case)
|
||||
while match_length < 50:
|
||||
j = i - match_length
|
||||
if j < 0:
|
||||
# Start of input reached.
|
||||
break
|
||||
|
||||
previous_token = input_ids_row[-(match_length+1)].item()
|
||||
if input_ids_row[j] != previous_token:
|
||||
previous_token = input_ids[-(match_length + 1)]
|
||||
if input_ids[j] != previous_token:
|
||||
# Start of match reached.
|
||||
break
|
||||
|
||||
@ -355,14 +359,14 @@ class RepetitionPenaltyLogitsProcessorWithRange(LogitsProcessor):
|
||||
return scores
|
||||
|
||||
|
||||
def get_logits_warper_patch(self, generation_config):
|
||||
def get_logits_warper_patch(self, generation_config, **kwargs):
|
||||
|
||||
# Parameter sanitization
|
||||
if isinstance(generation_config.temperature, int):
|
||||
generation_config.temperature = float(generation_config.temperature) # Must be float
|
||||
|
||||
# Get the original warpers
|
||||
warpers = self._get_logits_warper_old(generation_config)
|
||||
warpers = self._get_logits_warper_old(generation_config, **kwargs)
|
||||
|
||||
# Replace temperature with our modified class.
|
||||
# Currently, it behaves identically to the original.
|
||||
|
||||
@ -106,6 +106,7 @@ group.add_argument('--trust-remote-code', action='store_true', help='Set trust_r
|
||||
group.add_argument('--force-safetensors', action='store_true', help='Set use_safetensors=True while loading the model. This prevents arbitrary code execution.')
|
||||
group.add_argument('--no_use_fast', action='store_true', help='Set use_fast=False while loading the tokenizer (it\'s True by default). Use this if you have any problems related to use_fast.')
|
||||
group.add_argument('--use_flash_attention_2', action='store_true', help='Set use_flash_attention_2=True while loading the model.')
|
||||
group.add_argument('--use_eager_attention', action='store_true', help='Set attn_implementation= eager while loading the model.')
|
||||
|
||||
# bitsandbytes 4-bit
|
||||
group = parser.add_argument_group('bitsandbytes 4-bit')
|
||||
@ -142,6 +143,8 @@ group.add_argument('--autosplit', action='store_true', help='Autosplit the model
|
||||
group.add_argument('--max_seq_len', type=int, default=2048, help='Maximum sequence length.')
|
||||
group.add_argument('--cfg-cache', action='store_true', help='ExLlamav2_HF: Create an additional cache for CFG negative prompts. Necessary to use CFG with that loader.')
|
||||
group.add_argument('--no_flash_attn', action='store_true', help='Force flash-attention to not be used.')
|
||||
group.add_argument('--no_xformers', action='store_true', help='Force xformers to not be used.')
|
||||
group.add_argument('--no_sdpa', action='store_true', help='Force Torch SDPA to not be used.')
|
||||
group.add_argument('--cache_8bit', action='store_true', help='Use 8-bit cache to save VRAM.')
|
||||
group.add_argument('--cache_4bit', action='store_true', help='Use Q4 cache to save VRAM.')
|
||||
group.add_argument('--num_experts_per_token', type=int, default=2, help='Number of experts to use for generation. Applies to MoE models like Mixtral.')
|
||||
@ -165,6 +168,10 @@ group.add_argument('--no_inject_fused_attention', action='store_true', help='Dis
|
||||
group = parser.add_argument_group('HQQ')
|
||||
group.add_argument('--hqq-backend', type=str, default='PYTORCH_COMPILE', help='Backend for the HQQ loader. Valid options: PYTORCH, PYTORCH_COMPILE, ATEN.')
|
||||
|
||||
# TensorRT-LLM
|
||||
group = parser.add_argument_group('TensorRT-LLM')
|
||||
group.add_argument('--cpp-runner', action='store_true', help='Use the ModelRunnerCpp runner, which is faster than the default ModelRunner but doesn\'t support streaming yet.')
|
||||
|
||||
# DeepSpeed
|
||||
group = parser.add_argument_group('DeepSpeed')
|
||||
group.add_argument('--deepspeed', action='store_true', help='Enable the use of DeepSpeed ZeRO-3 for inference via the Transformers integration.')
|
||||
@ -263,6 +270,8 @@ def fix_loader_name(name):
|
||||
return 'AutoAWQ'
|
||||
elif name in ['hqq']:
|
||||
return 'HQQ'
|
||||
elif name in ['tensorrt', 'tensorrtllm', 'tensorrt_llm', 'tensorrt-llm', 'tensort', 'tensortllm']:
|
||||
return 'TensorRT-LLM'
|
||||
|
||||
|
||||
def add_extension(name, last=False):
|
||||
|
||||
131
modules/tensorrt_llm.py
Normal file
131
modules/tensorrt_llm.py
Normal file
@ -0,0 +1,131 @@
|
||||
from pathlib import Path
|
||||
|
||||
import tensorrt_llm
|
||||
import torch
|
||||
from tensorrt_llm.runtime import ModelRunner, ModelRunnerCpp
|
||||
|
||||
from modules import shared
|
||||
from modules.logging_colors import logger
|
||||
from modules.text_generation import (
|
||||
get_max_prompt_length,
|
||||
get_reply_from_output_ids
|
||||
)
|
||||
|
||||
|
||||
class TensorRTLLMModel:
|
||||
def __init__(self):
|
||||
pass
|
||||
|
||||
@classmethod
|
||||
def from_pretrained(self, path_to_model):
|
||||
|
||||
path_to_model = Path(f'{shared.args.model_dir}') / Path(path_to_model)
|
||||
runtime_rank = tensorrt_llm.mpi_rank()
|
||||
|
||||
# Define model settings
|
||||
runner_kwargs = dict(
|
||||
engine_dir=str(path_to_model),
|
||||
lora_dir=None,
|
||||
rank=runtime_rank,
|
||||
debug_mode=False,
|
||||
lora_ckpt_source="hf",
|
||||
)
|
||||
|
||||
if shared.args.cpp_runner:
|
||||
logger.info("TensorRT-LLM: Using \"ModelRunnerCpp\"")
|
||||
runner_kwargs.update(
|
||||
max_batch_size=1,
|
||||
max_input_len=shared.args.max_seq_len - 512,
|
||||
max_output_len=512,
|
||||
max_beam_width=1,
|
||||
max_attention_window_size=None,
|
||||
sink_token_length=None,
|
||||
)
|
||||
else:
|
||||
logger.info("TensorRT-LLM: Using \"ModelRunner\"")
|
||||
|
||||
# Load the model
|
||||
runner_cls = ModelRunnerCpp if shared.args.cpp_runner else ModelRunner
|
||||
runner = runner_cls.from_dir(**runner_kwargs)
|
||||
|
||||
result = self()
|
||||
result.model = runner
|
||||
result.runtime_rank = runtime_rank
|
||||
|
||||
return result
|
||||
|
||||
def generate_with_streaming(self, prompt, state):
|
||||
batch_input_ids = []
|
||||
input_ids = shared.tokenizer.encode(
|
||||
prompt,
|
||||
add_special_tokens=True,
|
||||
truncation=False,
|
||||
)
|
||||
input_ids = torch.tensor(input_ids, dtype=torch.int32)
|
||||
input_ids = input_ids[-get_max_prompt_length(state):] # Apply truncation_length
|
||||
batch_input_ids.append(input_ids)
|
||||
|
||||
if shared.args.cpp_runner:
|
||||
max_new_tokens = min(512, state['max_new_tokens'])
|
||||
elif state['auto_max_new_tokens']:
|
||||
max_new_tokens = state['truncation_length'] - input_ids.shape[-1]
|
||||
else:
|
||||
max_new_tokens = state['max_new_tokens']
|
||||
|
||||
with torch.no_grad():
|
||||
generator = self.model.generate(
|
||||
batch_input_ids,
|
||||
max_new_tokens=max_new_tokens,
|
||||
max_attention_window_size=None,
|
||||
sink_token_length=None,
|
||||
end_id=shared.tokenizer.eos_token_id if not state['ban_eos_token'] else -1,
|
||||
pad_id=shared.tokenizer.pad_token_id or shared.tokenizer.eos_token_id,
|
||||
temperature=state['temperature'],
|
||||
top_k=state['top_k'],
|
||||
top_p=state['top_p'],
|
||||
num_beams=1,
|
||||
length_penalty=1.0,
|
||||
repetition_penalty=state['repetition_penalty'],
|
||||
presence_penalty=state['presence_penalty'],
|
||||
frequency_penalty=state['frequency_penalty'],
|
||||
stop_words_list=None,
|
||||
bad_words_list=None,
|
||||
lora_uids=None,
|
||||
prompt_table_path=None,
|
||||
prompt_tasks=None,
|
||||
streaming=not shared.args.cpp_runner,
|
||||
output_sequence_lengths=True,
|
||||
return_dict=True,
|
||||
medusa_choices=None
|
||||
)
|
||||
|
||||
torch.cuda.synchronize()
|
||||
|
||||
cumulative_reply = ''
|
||||
starting_from = batch_input_ids[0].shape[-1]
|
||||
|
||||
if shared.args.cpp_runner:
|
||||
sequence_length = generator['sequence_lengths'][0].item()
|
||||
output_ids = generator['output_ids'][0][0][:sequence_length].tolist()
|
||||
|
||||
cumulative_reply += get_reply_from_output_ids(output_ids, state, starting_from=starting_from)
|
||||
starting_from = sequence_length
|
||||
yield cumulative_reply
|
||||
else:
|
||||
for curr_outputs in generator:
|
||||
if shared.stop_everything:
|
||||
break
|
||||
|
||||
sequence_length = curr_outputs['sequence_lengths'][0].item()
|
||||
output_ids = curr_outputs['output_ids'][0][0][:sequence_length].tolist()
|
||||
|
||||
cumulative_reply += get_reply_from_output_ids(output_ids, state, starting_from=starting_from)
|
||||
starting_from = sequence_length
|
||||
yield cumulative_reply
|
||||
|
||||
def generate(self, prompt, state):
|
||||
output = ''
|
||||
for output in self.generate_with_streaming(prompt, state):
|
||||
pass
|
||||
|
||||
return output
|
||||
@ -54,7 +54,7 @@ def _generate_reply(question, state, stopping_strings=None, is_chat=False, escap
|
||||
yield ''
|
||||
return
|
||||
|
||||
if shared.model.__class__.__name__ in ['LlamaCppModel', 'Exllamav2Model']:
|
||||
if shared.model.__class__.__name__ in ['LlamaCppModel', 'Exllamav2Model', 'TensorRTLLMModel']:
|
||||
generate_func = generate_reply_custom
|
||||
else:
|
||||
generate_func = generate_reply_HF
|
||||
@ -132,14 +132,14 @@ def encode(prompt, add_special_tokens=True, add_bos_token=True, truncation_lengt
|
||||
if shared.tokenizer is None:
|
||||
raise ValueError('No tokenizer is loaded')
|
||||
|
||||
if shared.model.__class__.__name__ in ['LlamaCppModel', 'Exllamav2Model']:
|
||||
if shared.model.__class__.__name__ in ['LlamaCppModel', 'Exllamav2Model', 'TensorRTLLMModel']:
|
||||
input_ids = shared.tokenizer.encode(str(prompt))
|
||||
if shared.model.__class__.__name__ not in ['Exllamav2Model']:
|
||||
input_ids = np.array(input_ids).reshape(1, len(input_ids))
|
||||
else:
|
||||
input_ids = shared.tokenizer.encode(str(prompt), return_tensors='pt', add_special_tokens=add_special_tokens)
|
||||
|
||||
if hasattr(shared.tokenizer, 'bos_token_id'):
|
||||
if hasattr(shared.tokenizer, 'bos_token_id') and shared.tokenizer.bos_token_id is not None:
|
||||
if add_bos_token:
|
||||
if (len(input_ids[0]) > 0 and input_ids[0][0] != shared.tokenizer.bos_token_id) or len(input_ids[0]) == 0:
|
||||
# Add a missing bos token (it may not have been added due to faulty model metadata)
|
||||
@ -158,7 +158,7 @@ def encode(prompt, add_special_tokens=True, add_bos_token=True, truncation_lengt
|
||||
if truncation_length is not None:
|
||||
input_ids = input_ids[:, -truncation_length:]
|
||||
|
||||
if shared.model.__class__.__name__ in ['LlamaCppModel', 'Exllamav2Model'] or shared.args.cpu:
|
||||
if shared.model.__class__.__name__ in ['LlamaCppModel', 'Exllamav2Model', 'TensorRTLLMModel'] or shared.args.cpu:
|
||||
return input_ids
|
||||
elif shared.args.deepspeed:
|
||||
import deepspeed
|
||||
|
||||
@ -43,6 +43,11 @@ theme = gr.themes.Default(
|
||||
body_text_color_subdued='#484848',
|
||||
background_fill_secondary='#eaeaea',
|
||||
background_fill_primary='var(--neutral-50)',
|
||||
body_background_fill="white",
|
||||
block_background_fill="#f4f4f4",
|
||||
body_text_color="#333",
|
||||
button_secondary_background_fill="#f4f4f4",
|
||||
button_secondary_border_color="var(--border-color-primary)"
|
||||
)
|
||||
|
||||
if Path("notification.mp3").exists():
|
||||
@ -64,13 +69,13 @@ def list_model_elements():
|
||||
'trust_remote_code',
|
||||
'no_use_fast',
|
||||
'use_flash_attention_2',
|
||||
'use_eager_attention',
|
||||
'load_in_4bit',
|
||||
'compute_dtype',
|
||||
'quant_type',
|
||||
'use_double_quant',
|
||||
'wbits',
|
||||
'groupsize',
|
||||
'pre_layer',
|
||||
'triton',
|
||||
'desc_act',
|
||||
'no_inject_fused_attention',
|
||||
@ -80,6 +85,8 @@ def list_model_elements():
|
||||
'disable_exllamav2',
|
||||
'cfg_cache',
|
||||
'no_flash_attn',
|
||||
'no_xformers',
|
||||
'no_sdpa',
|
||||
'num_experts_per_token',
|
||||
'cache_8bit',
|
||||
'cache_4bit',
|
||||
@ -103,10 +110,11 @@ def list_model_elements():
|
||||
'no_offload_kqv',
|
||||
'row_split',
|
||||
'tensorcores',
|
||||
'flash-attn',
|
||||
'flash_attn',
|
||||
'streaming_llm',
|
||||
'attention_sink_size',
|
||||
'hqq_backend',
|
||||
'cpp_runner',
|
||||
]
|
||||
if is_torch_xpu_available():
|
||||
for i in range(torch.xpu.device_count()):
|
||||
|
||||
@ -19,7 +19,7 @@ def create_ui():
|
||||
mu = shared.args.multi_user
|
||||
|
||||
shared.gradio['Chat input'] = gr.State()
|
||||
shared.gradio['history'] = gr.State({'internal': [], 'visible': []})
|
||||
shared.gradio['history'] = gr.JSON({'internal': [], 'visible': []}, visible=False)
|
||||
|
||||
with gr.Tab('Chat', elem_id='chat-tab', elem_classes=("old-ui" if shared.args.chat_buttons else None)):
|
||||
with gr.Row():
|
||||
@ -62,9 +62,6 @@ def create_ui():
|
||||
|
||||
with gr.Row(elem_id='past-chats-row', elem_classes=['pretty_scrollbar']):
|
||||
with gr.Column():
|
||||
with gr.Row():
|
||||
shared.gradio['unique_id'] = gr.Dropdown(label='Past chats', elem_classes=['slim-dropdown'], interactive=not mu)
|
||||
|
||||
with gr.Row():
|
||||
shared.gradio['rename_chat'] = gr.Button('Rename', elem_classes='refresh-button', interactive=not mu)
|
||||
shared.gradio['delete_chat'] = gr.Button('🗑️', elem_classes='refresh-button', interactive=not mu)
|
||||
@ -74,22 +71,27 @@ def create_ui():
|
||||
|
||||
with gr.Row(elem_id='rename-row'):
|
||||
shared.gradio['rename_to'] = gr.Textbox(label='Rename to:', placeholder='New name', visible=False, elem_classes=['no-background'])
|
||||
with gr.Row():
|
||||
shared.gradio['rename_to-confirm'] = gr.Button('Confirm', visible=False, elem_classes=['refresh-button', 'focus-on-chat-input'])
|
||||
shared.gradio['rename_to-cancel'] = gr.Button('Cancel', visible=False, elem_classes=['refresh-button', 'focus-on-chat-input'])
|
||||
|
||||
gr.Markdown("Past chats")
|
||||
with gr.Row():
|
||||
shared.gradio['unique_id'] = gr.Radio(label="", elem_classes=['slim-dropdown', 'pretty_scrollbar'], interactive=not mu, elem_id='past-chats')
|
||||
|
||||
with gr.Row(elem_id='chat-controls', elem_classes=['pretty_scrollbar']):
|
||||
with gr.Column():
|
||||
with gr.Row():
|
||||
shared.gradio['start_with'] = gr.Textbox(label='Start reply with', placeholder='Sure thing!', value=shared.settings['start_with'], elem_classes=['add_scrollbar'])
|
||||
|
||||
with gr.Row():
|
||||
shared.gradio['mode'] = gr.Radio(choices=['chat', 'chat-instruct', 'instruct'], value='chat', label='Mode', info='Defines how the chat prompt is generated. In instruct and chat-instruct modes, the instruction template selected under Parameters > Instruction template must match the current model.', elem_id='chat-mode')
|
||||
shared.gradio['mode'] = gr.Radio(choices=['chat', 'chat-instruct', 'instruct'], label='Mode', info='Defines how the chat prompt is generated. In instruct and chat-instruct modes, the instruction template Parameters > Instruction template is used.', elem_id='chat-mode')
|
||||
|
||||
with gr.Row():
|
||||
shared.gradio['chat_style'] = gr.Dropdown(choices=utils.get_available_chat_styles(), label='Chat style', value=shared.settings['chat_style'], visible=shared.settings['mode'] != 'instruct')
|
||||
|
||||
with gr.Row():
|
||||
shared.gradio['chat-instruct_command'] = gr.Textbox(value=shared.settings['chat-instruct_command'], lines=16, label='Command for chat-instruct mode', info='<|character|> and <|prompt|> get replaced with the bot name and the regular chat prompt respectively.', visible=False, elem_classes=['add_scrollbar'])
|
||||
shared.gradio['chat-instruct_command'] = gr.Textbox(value=shared.settings['chat-instruct_command'], lines=12, label='Command for chat-instruct mode', info='<|character|> and <|prompt|> get replaced with the bot name and the regular chat prompt respectively.', visible=False, elem_classes=['add_scrollbar'])
|
||||
|
||||
|
||||
def create_chat_settings_ui():
|
||||
@ -101,7 +103,7 @@ def create_chat_settings_ui():
|
||||
with gr.Row():
|
||||
shared.gradio['character_menu'] = gr.Dropdown(value=None, choices=utils.get_available_characters(), label='Character', elem_id='character-menu', info='Used in chat and chat-instruct modes.', elem_classes='slim-dropdown')
|
||||
ui.create_refresh_button(shared.gradio['character_menu'], lambda: None, lambda: {'choices': utils.get_available_characters()}, 'refresh-button', interactive=not mu)
|
||||
shared.gradio['save_character'] = gr.Button('💾', elem_classes='refresh-button', interactive=not mu)
|
||||
shared.gradio['save_character'] = gr.Button('💾', elem_classes='refresh-button', elem_id="save-character", interactive=not mu)
|
||||
shared.gradio['delete_character'] = gr.Button('🗑️', elem_classes='refresh-button', interactive=not mu)
|
||||
|
||||
shared.gradio['name2'] = gr.Textbox(value='', lines=1, label='Character\'s name')
|
||||
@ -181,7 +183,7 @@ def create_event_handlers():
|
||||
chat.generate_chat_reply_wrapper, gradio(inputs), gradio('display', 'history'), show_progress=False).then(
|
||||
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
|
||||
chat.save_history, gradio('history', 'unique_id', 'character_menu', 'mode'), None).then(
|
||||
lambda: None, None, None, js=f'() => {{{ui.audio_notification_js}}}')
|
||||
None, None, None, js=f'() => {{{ui.audio_notification_js}}}')
|
||||
|
||||
shared.gradio['textbox'].submit(
|
||||
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
|
||||
@ -189,28 +191,28 @@ def create_event_handlers():
|
||||
chat.generate_chat_reply_wrapper, gradio(inputs), gradio('display', 'history'), show_progress=False).then(
|
||||
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
|
||||
chat.save_history, gradio('history', 'unique_id', 'character_menu', 'mode'), None).then(
|
||||
lambda: None, None, None, js=f'() => {{{ui.audio_notification_js}}}')
|
||||
None, None, None, js=f'() => {{{ui.audio_notification_js}}}')
|
||||
|
||||
shared.gradio['Regenerate'].click(
|
||||
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
|
||||
partial(chat.generate_chat_reply_wrapper, regenerate=True), gradio(inputs), gradio('display', 'history'), show_progress=False).then(
|
||||
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
|
||||
chat.save_history, gradio('history', 'unique_id', 'character_menu', 'mode'), None).then(
|
||||
lambda: None, None, None, js=f'() => {{{ui.audio_notification_js}}}')
|
||||
None, None, None, js=f'() => {{{ui.audio_notification_js}}}')
|
||||
|
||||
shared.gradio['Continue'].click(
|
||||
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
|
||||
partial(chat.generate_chat_reply_wrapper, _continue=True), gradio(inputs), gradio('display', 'history'), show_progress=False).then(
|
||||
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
|
||||
chat.save_history, gradio('history', 'unique_id', 'character_menu', 'mode'), None).then(
|
||||
lambda: None, None, None, js=f'() => {{{ui.audio_notification_js}}}')
|
||||
None, None, None, js=f'() => {{{ui.audio_notification_js}}}')
|
||||
|
||||
shared.gradio['Impersonate'].click(
|
||||
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
|
||||
lambda x: x, gradio('textbox'), gradio('Chat input'), show_progress=False).then(
|
||||
chat.impersonate_wrapper, gradio(inputs), gradio('textbox', 'display'), show_progress=False).then(
|
||||
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
|
||||
lambda: None, None, None, js=f'() => {{{ui.audio_notification_js}}}')
|
||||
None, None, None, js=f'() => {{{ui.audio_notification_js}}}')
|
||||
|
||||
shared.gradio['Replace last reply'].click(
|
||||
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
|
||||
@ -252,7 +254,7 @@ def create_event_handlers():
|
||||
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
|
||||
chat.start_new_chat, gradio('interface_state'), gradio('history')).then(
|
||||
chat.redraw_html, gradio(reload_arr), gradio('display')).then(
|
||||
lambda x: gr.update(choices=(histories := chat.find_all_histories(x)), value=histories[0]), gradio('interface_state'), gradio('unique_id'))
|
||||
lambda x: gr.update(choices=(histories := chat.find_all_histories_with_first_prompts(x)), value=histories[0][1]), gradio('interface_state'), gradio('unique_id'), show_progress=False)
|
||||
|
||||
shared.gradio['delete_chat'].click(lambda: [gr.update(visible=True), gr.update(visible=False), gr.update(visible=True)], None, gradio(clear_arr))
|
||||
shared.gradio['delete_chat-cancel'].click(lambda: [gr.update(visible=False), gr.update(visible=True), gr.update(visible=False)], None, gradio(clear_arr))
|
||||
@ -260,12 +262,12 @@ def create_event_handlers():
|
||||
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
|
||||
lambda x, y: str(chat.find_all_histories(x).index(y)), gradio('interface_state', 'unique_id'), gradio('temporary_text')).then(
|
||||
chat.delete_history, gradio('unique_id', 'character_menu', 'mode'), None).then(
|
||||
chat.load_history_after_deletion, gradio('interface_state', 'temporary_text'), gradio('history', 'unique_id')).then(
|
||||
chat.load_history_after_deletion, gradio('interface_state', 'temporary_text'), gradio('history', 'unique_id'), show_progress=False).then(
|
||||
chat.redraw_html, gradio(reload_arr), gradio('display')).then(
|
||||
lambda: [gr.update(visible=False), gr.update(visible=True), gr.update(visible=False)], None, gradio(clear_arr))
|
||||
|
||||
shared.gradio['rename_chat'].click(
|
||||
lambda x: x, gradio('unique_id'), gradio('rename_to')).then(
|
||||
lambda: "My New Chat", None, gradio('rename_to')).then(
|
||||
lambda: [gr.update(visible=True)] * 3, None, gradio('rename_to', 'rename_to-confirm', 'rename_to-cancel'), show_progress=False)
|
||||
|
||||
shared.gradio['rename_to-cancel'].click(
|
||||
@ -274,36 +276,38 @@ def create_event_handlers():
|
||||
shared.gradio['rename_to-confirm'].click(
|
||||
chat.rename_history, gradio('unique_id', 'rename_to', 'character_menu', 'mode'), None).then(
|
||||
lambda: [gr.update(visible=False)] * 3, None, gradio('rename_to', 'rename_to-confirm', 'rename_to-cancel'), show_progress=False).then(
|
||||
lambda x, y: gr.update(choices=chat.find_all_histories(x), value=y), gradio('interface_state', 'rename_to'), gradio('unique_id'))
|
||||
lambda x, y: gr.update(choices=chat.find_all_histories_with_first_prompts(x), value=y), gradio('interface_state', 'rename_to'), gradio('unique_id'))
|
||||
|
||||
shared.gradio['rename_to'].submit(
|
||||
chat.rename_history, gradio('unique_id', 'rename_to', 'character_menu', 'mode'), None).then(
|
||||
lambda: [gr.update(visible=False)] * 3, None, gradio('rename_to', 'rename_to-confirm', 'rename_to-cancel'), show_progress=False).then(
|
||||
lambda x, y: gr.update(choices=chat.find_all_histories(x), value=y), gradio('interface_state', 'rename_to'), gradio('unique_id'))
|
||||
lambda x, y: gr.update(choices=chat.find_all_histories_with_first_prompts(x), value=y), gradio('interface_state', 'rename_to'), gradio('unique_id'))
|
||||
|
||||
shared.gradio['load_chat_history'].upload(
|
||||
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
|
||||
chat.start_new_chat, gradio('interface_state'), gradio('history')).then(
|
||||
chat.load_history_json, gradio('load_chat_history', 'history'), gradio('history')).then(
|
||||
chat.redraw_html, gradio(reload_arr), gradio('display')).then(
|
||||
lambda x: gr.update(choices=(histories := chat.find_all_histories(x)), value=histories[0]), gradio('interface_state'), gradio('unique_id')).then(
|
||||
lambda x: gr.update(choices=(histories := chat.find_all_histories_with_first_prompts(x)), value=histories[0][1]), gradio('interface_state'), gradio('unique_id'), show_progress=False).then(
|
||||
chat.save_history, gradio('history', 'unique_id', 'character_menu', 'mode'), None).then(
|
||||
lambda: None, None, None, js=f'() => {{{ui.switch_tabs_js}; switch_to_chat()}}')
|
||||
None, None, None, js=f'() => {{{ui.switch_tabs_js}; switch_to_chat()}}')
|
||||
|
||||
shared.gradio['character_menu'].change(
|
||||
chat.load_character, gradio('character_menu', 'name1', 'name2'), gradio('name1', 'name2', 'character_picture', 'greeting', 'context')).success(
|
||||
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
|
||||
chat.load_latest_history, gradio('interface_state'), gradio('history')).then(
|
||||
chat.redraw_html, gradio(reload_arr), gradio('display')).then(
|
||||
lambda x: gr.update(choices=(histories := chat.find_all_histories(x)), value=histories[0]), gradio('interface_state'), gradio('unique_id')).then(
|
||||
lambda: None, None, None, js=f'() => {{{ui.update_big_picture_js}; updateBigPicture()}}')
|
||||
lambda x: gr.update(choices=(histories := chat.find_all_histories_with_first_prompts(x)), value=histories[0][1]), gradio('interface_state'), gradio('unique_id'), show_progress=False).then(
|
||||
None, None, None, js=f'() => {{{ui.update_big_picture_js}; updateBigPicture()}}')
|
||||
|
||||
shared.gradio['mode'].change(None, gradio('mode'), None, js="(mode) => {mode === 'instruct' ? document.getElementById('character-menu').parentNode.parentNode.style.display = 'none' : document.getElementById('character-menu').parentNode.parentNode.style.display = ''}")
|
||||
|
||||
shared.gradio['mode'].change(
|
||||
lambda x: [gr.update(visible=x != 'instruct'), gr.update(visible=x == 'chat-instruct')], gradio('mode'), gradio('chat_style', 'chat-instruct_command'), show_progress=False).then(
|
||||
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
|
||||
chat.load_latest_history, gradio('interface_state'), gradio('history')).then(
|
||||
chat.redraw_html, gradio(reload_arr), gradio('display')).then(
|
||||
lambda x: gr.update(choices=(histories := chat.find_all_histories(x)), value=histories[0]), gradio('interface_state'), gradio('unique_id'))
|
||||
lambda x: gr.update(choices=(histories := chat.find_all_histories_with_first_prompts(x)), value=histories[0][1]), gradio('interface_state'), gradio('unique_id'), show_progress=False)
|
||||
|
||||
shared.gradio['chat_style'].change(chat.redraw_html, gradio(reload_arr), gradio('display'))
|
||||
shared.gradio['Copy last reply'].click(chat.send_last_reply_to_input, gradio('history'), gradio('textbox'), show_progress=False)
|
||||
@ -336,11 +340,11 @@ def create_event_handlers():
|
||||
|
||||
shared.gradio['Submit character'].click(
|
||||
chat.upload_character, gradio('upload_json', 'upload_img_bot'), gradio('character_menu')).then(
|
||||
lambda: None, None, None, js=f'() => {{{ui.switch_tabs_js}; switch_to_character()}}')
|
||||
None, None, None, js=f'() => {{{ui.switch_tabs_js}; switch_to_character()}}')
|
||||
|
||||
shared.gradio['Submit tavern character'].click(
|
||||
chat.upload_tavern_character, gradio('upload_img_tavern', 'tavern_json'), gradio('character_menu')).then(
|
||||
lambda: None, None, None, js=f'() => {{{ui.switch_tabs_js}; switch_to_character()}}')
|
||||
None, None, None, js=f'() => {{{ui.switch_tabs_js}; switch_to_character()}}')
|
||||
|
||||
shared.gradio['upload_json'].upload(lambda: gr.update(interactive=True), None, gradio('Submit character'))
|
||||
shared.gradio['upload_json'].clear(lambda: gr.update(interactive=False), None, gradio('Submit character'))
|
||||
@ -354,28 +358,28 @@ def create_event_handlers():
|
||||
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
|
||||
lambda x: x.update({'mode': 'instruct', 'history': {'internal': [], 'visible': []}}), gradio('interface_state'), None).then(
|
||||
partial(chat.generate_chat_prompt, 'Input'), gradio('interface_state'), gradio('textbox-default')).then(
|
||||
lambda: None, None, None, js=f'() => {{{ui.switch_tabs_js}; switch_to_default()}}')
|
||||
None, None, None, js=f'() => {{{ui.switch_tabs_js}; switch_to_default()}}')
|
||||
|
||||
shared.gradio['send_instruction_to_notebook'].click(
|
||||
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
|
||||
lambda x: x.update({'mode': 'instruct', 'history': {'internal': [], 'visible': []}}), gradio('interface_state'), None).then(
|
||||
partial(chat.generate_chat_prompt, 'Input'), gradio('interface_state'), gradio('textbox-notebook')).then(
|
||||
lambda: None, None, None, js=f'() => {{{ui.switch_tabs_js}; switch_to_notebook()}}')
|
||||
None, None, None, js=f'() => {{{ui.switch_tabs_js}; switch_to_notebook()}}')
|
||||
|
||||
shared.gradio['send_instruction_to_negative_prompt'].click(
|
||||
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
|
||||
lambda x: x.update({'mode': 'instruct', 'history': {'internal': [], 'visible': []}}), gradio('interface_state'), None).then(
|
||||
partial(chat.generate_chat_prompt, 'Input'), gradio('interface_state'), gradio('negative_prompt')).then(
|
||||
lambda: None, None, None, js=f'() => {{{ui.switch_tabs_js}; switch_to_generation_parameters()}}')
|
||||
None, None, None, js=f'() => {{{ui.switch_tabs_js}; switch_to_generation_parameters()}}')
|
||||
|
||||
shared.gradio['send-chat-to-default'].click(
|
||||
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
|
||||
partial(chat.generate_chat_prompt, '', _continue=True), gradio('interface_state'), gradio('textbox-default')).then(
|
||||
lambda: None, None, None, js=f'() => {{{ui.switch_tabs_js}; switch_to_default()}}')
|
||||
None, None, None, js=f'() => {{{ui.switch_tabs_js}; switch_to_default()}}')
|
||||
|
||||
shared.gradio['send-chat-to-notebook'].click(
|
||||
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
|
||||
partial(chat.generate_chat_prompt, '', _continue=True), gradio('interface_state'), gradio('textbox-notebook')).then(
|
||||
lambda: None, None, None, js=f'() => {{{ui.switch_tabs_js}; switch_to_notebook()}}')
|
||||
None, None, None, js=f'() => {{{ui.switch_tabs_js}; switch_to_notebook()}}')
|
||||
|
||||
shared.gradio['show_controls'].change(lambda x: None, gradio('show_controls'), None, js=f'(x) => {{{ui.show_controls_js}; toggle_controls(x)}}')
|
||||
shared.gradio['show_controls'].change(None, gradio('show_controls'), None, js=f'(x) => {{{ui.show_controls_js}; toggle_controls(x)}}')
|
||||
|
||||
@ -16,7 +16,6 @@ outputs = ('output_textbox', 'html-default')
|
||||
def create_ui():
|
||||
mu = shared.args.multi_user
|
||||
with gr.Tab('Default', elem_id='default-tab'):
|
||||
shared.gradio['last_input-default'] = gr.State('')
|
||||
with gr.Row():
|
||||
with gr.Column():
|
||||
with gr.Row():
|
||||
@ -63,25 +62,23 @@ def create_ui():
|
||||
|
||||
def create_event_handlers():
|
||||
shared.gradio['Generate-default'].click(
|
||||
lambda x: x, gradio('textbox-default'), gradio('last_input-default')).then(
|
||||
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
|
||||
generate_reply_wrapper, gradio(inputs), gradio(outputs), show_progress=False).then(
|
||||
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
|
||||
lambda: None, None, None, js=f'() => {{{ui.audio_notification_js}}}')
|
||||
None, None, None, js=f'() => {{{ui.audio_notification_js}}}')
|
||||
|
||||
shared.gradio['textbox-default'].submit(
|
||||
lambda x: x, gradio('textbox-default'), gradio('last_input-default')).then(
|
||||
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
|
||||
generate_reply_wrapper, gradio(inputs), gradio(outputs), show_progress=False).then(
|
||||
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
|
||||
lambda: None, None, None, js=f'() => {{{ui.audio_notification_js}}}')
|
||||
None, None, None, js=f'() => {{{ui.audio_notification_js}}}')
|
||||
|
||||
shared.gradio['markdown_render-default'].click(lambda x: x, gradio('output_textbox'), gradio('markdown-default'), queue=False)
|
||||
shared.gradio['Continue-default'].click(
|
||||
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
|
||||
generate_reply_wrapper, [shared.gradio['output_textbox']] + gradio(inputs)[1:], gradio(outputs), show_progress=False).then(
|
||||
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
|
||||
lambda: None, None, None, js=f'() => {{{ui.audio_notification_js}}}')
|
||||
None, None, None, js=f'() => {{{ui.audio_notification_js}}}')
|
||||
|
||||
shared.gradio['Stop-default'].click(stop_everything_event, None, None, queue=False)
|
||||
shared.gradio['prompt_menu-default'].change(load_prompt, gradio('prompt_menu-default'), gradio('textbox-default'), show_progress=False)
|
||||
|
||||
@ -101,13 +101,12 @@ def create_ui():
|
||||
shared.gradio['threads_batch'] = gr.Slider(label="threads_batch", minimum=0, step=1, maximum=256, value=shared.args.threads_batch)
|
||||
shared.gradio['wbits'] = gr.Dropdown(label="wbits", choices=["None", 1, 2, 3, 4, 8], value=shared.args.wbits if shared.args.wbits > 0 else "None")
|
||||
shared.gradio['groupsize'] = gr.Dropdown(label="groupsize", choices=["None", 32, 64, 128, 1024], value=shared.args.groupsize if shared.args.groupsize > 0 else "None")
|
||||
shared.gradio['pre_layer'] = gr.Slider(label="pre_layer", minimum=0, maximum=100, value=shared.args.pre_layer[0] if shared.args.pre_layer is not None else 0)
|
||||
shared.gradio['gpu_split'] = gr.Textbox(label='gpu-split', info='Comma-separated list of VRAM (in GB) to use per GPU. Example: 20,7,7')
|
||||
shared.gradio['max_seq_len'] = gr.Slider(label='max_seq_len', minimum=0, maximum=shared.settings['truncation_length_max'], step=256, info='Context length. Try lowering this if you run out of memory while loading the model.', value=shared.args.max_seq_len)
|
||||
with gr.Blocks():
|
||||
shared.gradio['alpha_value'] = gr.Slider(label='alpha_value', minimum=1, maximum=8, step=0.05, info='Positional embeddings alpha factor for NTK RoPE scaling. Recommended values (NTKv1): 1.75 for 1.5x context, 2.5 for 2x context. Use either this or compress_pos_emb, not both.', value=shared.args.alpha_value)
|
||||
shared.gradio['rope_freq_base'] = gr.Slider(label='rope_freq_base', minimum=0, maximum=1000000, step=1000, info='If greater than 0, will be used instead of alpha_value. Those two are related by rope_freq_base = 10000 * alpha_value ^ (64 / 63)', value=shared.args.rope_freq_base)
|
||||
shared.gradio['compress_pos_emb'] = gr.Slider(label='compress_pos_emb', minimum=1, maximum=8, step=1, info='Positional embeddings compression factor. Should be set to (context length) / (model\'s original context length). Equal to 1/rope_freq_scale.', value=shared.args.compress_pos_emb)
|
||||
shared.gradio['rope_freq_base'] = gr.Slider(label='rope_freq_base', minimum=0, maximum=20000000, step=1000, info='If greater than 0, will be used instead of alpha_value. Those two are related by rope_freq_base = 10000 * alpha_value ^ (64 / 63)', value=shared.args.rope_freq_base)
|
||||
shared.gradio['compress_pos_emb'] = gr.Slider(label='compress_pos_emb', minimum=1, maximum=8, step=0.1, info='Positional embeddings compression factor. Should be set to (context length) / (model\'s original context length). Equal to 1/rope_freq_scale.', value=shared.args.compress_pos_emb)
|
||||
|
||||
shared.gradio['autogptq_info'] = gr.Markdown('ExLlamav2_HF is recommended over AutoGPTQ for models derived from Llama.')
|
||||
|
||||
@ -116,9 +115,12 @@ def create_ui():
|
||||
shared.gradio['load_in_4bit'] = gr.Checkbox(label="load-in-4bit", value=shared.args.load_in_4bit)
|
||||
shared.gradio['use_double_quant'] = gr.Checkbox(label="use_double_quant", value=shared.args.use_double_quant)
|
||||
shared.gradio['use_flash_attention_2'] = gr.Checkbox(label="use_flash_attention_2", value=shared.args.use_flash_attention_2, info='Set use_flash_attention_2=True while loading the model.')
|
||||
shared.gradio['flash-attn'] = gr.Checkbox(label="flash-attn", value=shared.args.flash_attn, info='Use flash-attention.')
|
||||
shared.gradio['use_eager_attention'] = gr.Checkbox(label="use_eager_attention", value=shared.args.use_eager_attention, info='Set attn_implementation= eager while loading the model.')
|
||||
shared.gradio['flash_attn'] = gr.Checkbox(label="flash_attn", value=shared.args.flash_attn, info='Use flash-attention.')
|
||||
shared.gradio['auto_devices'] = gr.Checkbox(label="auto-devices", value=shared.args.auto_devices)
|
||||
shared.gradio['tensorcores'] = gr.Checkbox(label="tensorcores", value=shared.args.tensorcores, info='NVIDIA only: use llama-cpp-python compiled with tensor cores support. This increases performance on RTX cards.')
|
||||
shared.gradio['cache_8bit'] = gr.Checkbox(label="cache_8bit", value=shared.args.cache_8bit, info='Use 8-bit cache to save VRAM.')
|
||||
shared.gradio['cache_4bit'] = gr.Checkbox(label="cache_4bit", value=shared.args.cache_4bit, info='Use Q4 cache to save VRAM.')
|
||||
shared.gradio['streaming_llm'] = gr.Checkbox(label="streaming_llm", value=shared.args.streaming_llm, info='(experimental) Activate StreamingLLM to avoid re-evaluating the entire prompt when old messages are removed.')
|
||||
shared.gradio['attention_sink_size'] = gr.Number(label="attention_sink_size", value=shared.args.attention_sink_size, precision=0, info='StreamingLLM: number of sink tokens. Only used if the trimmed prompt doesn\'t share a prefix with the old prompt.')
|
||||
shared.gradio['cpu'] = gr.Checkbox(label="cpu", value=shared.args.cpu, info='llama.cpp: Use llama-cpp-python compiled without GPU acceleration. Transformers: use PyTorch in CPU mode.')
|
||||
@ -135,11 +137,12 @@ def create_ui():
|
||||
shared.gradio['numa'] = gr.Checkbox(label="numa", value=shared.args.numa, info='NUMA support can help on some systems with non-uniform memory access.')
|
||||
shared.gradio['disk'] = gr.Checkbox(label="disk", value=shared.args.disk)
|
||||
shared.gradio['bf16'] = gr.Checkbox(label="bf16", value=shared.args.bf16)
|
||||
shared.gradio['cache_8bit'] = gr.Checkbox(label="cache_8bit", value=shared.args.cache_8bit, info='Use 8-bit cache to save VRAM.')
|
||||
shared.gradio['cache_4bit'] = gr.Checkbox(label="cache_4bit", value=shared.args.cache_4bit, info='Use Q4 cache to save VRAM.')
|
||||
shared.gradio['autosplit'] = gr.Checkbox(label="autosplit", value=shared.args.autosplit, info='Automatically split the model tensors across the available GPUs.')
|
||||
shared.gradio['no_flash_attn'] = gr.Checkbox(label="no_flash_attn", value=shared.args.no_flash_attn, info='Force flash-attention to not be used.')
|
||||
shared.gradio['no_flash_attn'] = gr.Checkbox(label="no_flash_attn", value=shared.args.no_flash_attn)
|
||||
shared.gradio['no_xformers'] = gr.Checkbox(label="no_xformers", value=shared.args.no_xformers)
|
||||
shared.gradio['no_sdpa'] = gr.Checkbox(label="no_sdpa", value=shared.args.no_sdpa)
|
||||
shared.gradio['cfg_cache'] = gr.Checkbox(label="cfg-cache", value=shared.args.cfg_cache, info='Necessary to use CFG with this loader.')
|
||||
shared.gradio['cpp_runner'] = gr.Checkbox(label="cpp-runner", value=shared.args.cpp_runner, info='Enable inference with ModelRunnerCpp, which is faster than the default ModelRunner.')
|
||||
shared.gradio['num_experts_per_token'] = gr.Number(label="Number of experts per token", value=shared.args.num_experts_per_token, info='Only applies to MoE models like Mixtral.')
|
||||
with gr.Blocks():
|
||||
shared.gradio['trust_remote_code'] = gr.Checkbox(label="trust-remote-code", value=shared.args.trust_remote_code, info='Set trust_remote_code=True while loading the tokenizer/model. To enable this option, start the web UI with the --trust-remote-code flag.', interactive=shared.args.trust_remote_code)
|
||||
@ -148,9 +151,9 @@ def create_ui():
|
||||
|
||||
shared.gradio['disable_exllama'] = gr.Checkbox(label="disable_exllama", value=shared.args.disable_exllama, info='Disable ExLlama kernel for GPTQ models.')
|
||||
shared.gradio['disable_exllamav2'] = gr.Checkbox(label="disable_exllamav2", value=shared.args.disable_exllamav2, info='Disable ExLlamav2 kernel for GPTQ models.')
|
||||
shared.gradio['gptq_for_llama_info'] = gr.Markdown('Legacy loader for compatibility with older GPUs. ExLlamav2_HF or AutoGPTQ are preferred for GPTQ models when supported.')
|
||||
shared.gradio['exllamav2_info'] = gr.Markdown("ExLlamav2_HF is recommended over ExLlamav2 for better integration with extensions and more consistent sampling behavior across loaders.")
|
||||
shared.gradio['llamacpp_HF_info'] = gr.Markdown("llamacpp_HF loads llama.cpp as a Transformers model. To use it, you need to place your GGUF in a subfolder of models/ with the necessary tokenizer files.\n\nYou can use the \"llamacpp_HF creator\" menu to do that automatically.")
|
||||
shared.gradio['tensorrt_llm_info'] = gr.Markdown('* TensorRT-LLM has to be installed manually in a separate Python 3.10 environment at the moment. For a guide, consult the description of [this PR](https://github.com/oobabooga/text-generation-webui/pull/5715). \n\n* `max_seq_len` is only used when `cpp-runner` is checked.\n\n* `cpp_runner` does not support streaming at the moment.')
|
||||
|
||||
with gr.Column():
|
||||
with gr.Row():
|
||||
|
||||
@ -67,14 +67,14 @@ def create_event_handlers():
|
||||
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
|
||||
generate_reply_wrapper, gradio(inputs), gradio(outputs), show_progress=False).then(
|
||||
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
|
||||
lambda: None, None, None, js=f'() => {{{ui.audio_notification_js}}}')
|
||||
None, None, None, js=f'() => {{{ui.audio_notification_js}}}')
|
||||
|
||||
shared.gradio['textbox-notebook'].submit(
|
||||
lambda x: x, gradio('textbox-notebook'), gradio('last_input-notebook')).then(
|
||||
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
|
||||
generate_reply_wrapper, gradio(inputs), gradio(outputs), show_progress=False).then(
|
||||
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
|
||||
lambda: None, None, None, js=f'() => {{{ui.audio_notification_js}}}')
|
||||
None, None, None, js=f'() => {{{ui.audio_notification_js}}}')
|
||||
|
||||
shared.gradio['Undo'].click(lambda x: x, gradio('last_input-notebook'), gradio('textbox-notebook'), show_progress=False)
|
||||
shared.gradio['markdown_render-notebook'].click(lambda x: x, gradio('textbox-notebook'), gradio('markdown-notebook'), queue=False)
|
||||
@ -83,7 +83,7 @@ def create_event_handlers():
|
||||
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
|
||||
generate_reply_wrapper, gradio(inputs), gradio(outputs), show_progress=False).then(
|
||||
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
|
||||
lambda: None, None, None, js=f'() => {{{ui.audio_notification_js}}}')
|
||||
None, None, None, js=f'() => {{{ui.audio_notification_js}}}')
|
||||
|
||||
shared.gradio['Stop-notebook'].click(stop_everything_event, None, None, queue=False)
|
||||
shared.gradio['prompt_menu-notebook'].change(load_prompt, gradio('prompt_menu-notebook'), gradio('textbox-notebook'), show_progress=False)
|
||||
|
||||
@ -40,7 +40,6 @@ def create_ui(default_preset):
|
||||
shared.gradio['do_sample'] = gr.Checkbox(value=generate_params['do_sample'], label='do_sample')
|
||||
|
||||
with gr.Blocks():
|
||||
gr.Markdown("[DRY sequence repetition penalty](https://github.com/oobabooga/text-generation-webui/pull/5677)")
|
||||
shared.gradio['dry_multiplier'] = gr.Slider(0, 5, value=generate_params['dry_multiplier'], step=0.01, label='dry_multiplier', info='Set to value > 0 to enable DRY. Controls the magnitude of the penalty for the shortest penalized sequences.')
|
||||
shared.gradio['dry_base'] = gr.Slider(1, 4, value=generate_params['dry_base'], step=0.01, label='dry_base', info='Controls how fast the penalty grows with increasing sequence length.')
|
||||
shared.gradio['dry_allowed_length'] = gr.Slider(1, 20, value=generate_params['dry_allowed_length'], step=1, label='dry_allowed_length', info='Longest sequence that can be repeated without being penalized.')
|
||||
|
||||
@ -32,10 +32,10 @@ def create_ui():
|
||||
# Reset interface event
|
||||
shared.gradio['reset_interface'].click(
|
||||
set_interface_arguments, gradio('extensions_menu', 'bool_menu'), None).then(
|
||||
lambda: None, None, None, js='() => {document.body.innerHTML=\'<h1 style="font-family:monospace;padding-top:20%;margin:0;height:100vh;color:lightgray;text-align:center;background:var(--body-background-fill)">Reloading...</h1>\'; setTimeout(function(){location.reload()},2500); return []}')
|
||||
None, None, None, js='() => {document.body.innerHTML=\'<h1 style="font-family:monospace;padding-top:20%;margin:0;height:100vh;color:lightgray;text-align:center;background:var(--body-background-fill)">Reloading...</h1>\'; setTimeout(function(){location.reload()},2500); return []}')
|
||||
|
||||
shared.gradio['toggle_dark_mode'].click(
|
||||
lambda: None, None, None, js='() => {document.getElementsByTagName("body")[0].classList.toggle("dark")}').then(
|
||||
None, None, None, js='() => {document.getElementsByTagName("body")[0].classList.toggle("dark")}').then(
|
||||
lambda x: 'dark' if x == 'light' else 'light', gradio('theme_state'), gradio('theme_state'))
|
||||
|
||||
shared.gradio['save_settings'].click(
|
||||
|
||||
@ -16,9 +16,9 @@ import sys
|
||||
|
||||
|
||||
# Define the required PyTorch version
|
||||
TORCH_VERSION = "2.2.1"
|
||||
TORCHVISION_VERSION = "0.17.1"
|
||||
TORCHAUDIO_VERSION = "2.2.1"
|
||||
TORCH_VERSION = "2.2.2"
|
||||
TORCHVISION_VERSION = "0.17.2"
|
||||
TORCHAUDIO_VERSION = "2.2.2"
|
||||
|
||||
# Environment
|
||||
script_dir = os.getcwd()
|
||||
@ -315,7 +315,7 @@ def install_webui():
|
||||
run_cmd("conda install -y libuv")
|
||||
|
||||
# Install the webui requirements
|
||||
update_requirements(initial_installation=True)
|
||||
update_requirements(initial_installation=True, pull=False)
|
||||
|
||||
|
||||
def get_extensions_names():
|
||||
|
||||
@ -1,13 +1,13 @@
|
||||
accelerate==0.30.*
|
||||
aqlm[gpu,cpu]==1.1.5; platform_system == "Linux"
|
||||
accelerate==0.32.*
|
||||
aqlm[gpu,cpu]==1.1.6; platform_system == "Linux"
|
||||
auto-gptq==0.7.1
|
||||
bitsandbytes==0.43.*
|
||||
colorama
|
||||
datasets
|
||||
einops
|
||||
gradio==4.26.*
|
||||
hqq==0.1.7.post2
|
||||
jinja2==3.1.2
|
||||
hqq==0.1.7.post3
|
||||
jinja2==3.1.4
|
||||
lm_eval==0.3.0
|
||||
markdown
|
||||
numba==0.59.*
|
||||
@ -24,7 +24,7 @@ safetensors==0.4.*
|
||||
scipy
|
||||
sentencepiece
|
||||
tensorboard
|
||||
transformers==4.41.*
|
||||
transformers==4.42.*
|
||||
tqdm
|
||||
wandb
|
||||
|
||||
@ -37,31 +37,31 @@ soundfile
|
||||
openai-whisper
|
||||
|
||||
# llama-cpp-python (CPU only, AVX2)
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.75+cpuavx2-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.75+cpuavx2-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.75+cpuavx2-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.75+cpuavx2-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.82+cpuavx2-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.82+cpuavx2-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.82+cpuavx2-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.82+cpuavx2-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
|
||||
|
||||
# llama-cpp-python (CUDA, no tensor cores)
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/textgen-webui/llama_cpp_python_cuda-0.2.75+cu121-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/textgen-webui/llama_cpp_python_cuda-0.2.75+cu121-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/textgen-webui/llama_cpp_python_cuda-0.2.75+cu121-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/textgen-webui/llama_cpp_python_cuda-0.2.75+cu121-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/textgen-webui/llama_cpp_python_cuda-0.2.82+cu121-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/textgen-webui/llama_cpp_python_cuda-0.2.82+cu121-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/textgen-webui/llama_cpp_python_cuda-0.2.82+cu121-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/textgen-webui/llama_cpp_python_cuda-0.2.82+cu121-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
|
||||
|
||||
# llama-cpp-python (CUDA, tensor cores)
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/textgen-webui/llama_cpp_python_cuda_tensorcores-0.2.75+cu121-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/textgen-webui/llama_cpp_python_cuda_tensorcores-0.2.75+cu121-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/textgen-webui/llama_cpp_python_cuda_tensorcores-0.2.75+cu121-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/textgen-webui/llama_cpp_python_cuda_tensorcores-0.2.75+cu121-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/textgen-webui/llama_cpp_python_cuda_tensorcores-0.2.82+cu121-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/textgen-webui/llama_cpp_python_cuda_tensorcores-0.2.82+cu121-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/textgen-webui/llama_cpp_python_cuda_tensorcores-0.2.82+cu121-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/textgen-webui/llama_cpp_python_cuda_tensorcores-0.2.82+cu121-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
|
||||
|
||||
# CUDA wheels
|
||||
https://github.com/oobabooga/exllamav2/releases/download/v0.0.20/exllamav2-0.0.20+cu121-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
|
||||
https://github.com/oobabooga/exllamav2/releases/download/v0.0.20/exllamav2-0.0.20+cu121-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
|
||||
https://github.com/oobabooga/exllamav2/releases/download/v0.0.20/exllamav2-0.0.20+cu121-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
|
||||
https://github.com/oobabooga/exllamav2/releases/download/v0.0.20/exllamav2-0.0.20+cu121-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
|
||||
https://github.com/oobabooga/exllamav2/releases/download/v0.0.20/exllamav2-0.0.20-py3-none-any.whl; platform_system == "Linux" and platform_machine != "x86_64"
|
||||
https://github.com/oobabooga/flash-attention/releases/download/v2.5.6/flash_attn-2.5.6+cu122torch2.2.0cxx11abiFALSE-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
|
||||
https://github.com/oobabooga/flash-attention/releases/download/v2.5.6/flash_attn-2.5.6+cu122torch2.2.0cxx11abiFALSE-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
|
||||
https://github.com/Dao-AILab/flash-attention/releases/download/v2.5.6/flash_attn-2.5.6+cu122torch2.2cxx11abiFALSE-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
|
||||
https://github.com/Dao-AILab/flash-attention/releases/download/v2.5.6/flash_attn-2.5.6+cu122torch2.2cxx11abiFALSE-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
|
||||
https://github.com/oobabooga/exllamav2/releases/download/v0.1.7/exllamav2-0.1.7+cu121.torch2.2.2-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
|
||||
https://github.com/oobabooga/exllamav2/releases/download/v0.1.7/exllamav2-0.1.7+cu121.torch2.2.2-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
|
||||
https://github.com/oobabooga/exllamav2/releases/download/v0.1.7/exllamav2-0.1.7+cu121.torch2.2.2-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
|
||||
https://github.com/oobabooga/exllamav2/releases/download/v0.1.7/exllamav2-0.1.7+cu121.torch2.2.2-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
|
||||
https://github.com/oobabooga/exllamav2/releases/download/v0.1.7/exllamav2-0.1.7-py3-none-any.whl; platform_system == "Linux" and platform_machine != "x86_64"
|
||||
https://github.com/oobabooga/flash-attention/releases/download/v2.6.1/flash_attn-2.6.1+cu122torch2.2.2cxx11abiFALSE-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
|
||||
https://github.com/oobabooga/flash-attention/releases/download/v2.6.1/flash_attn-2.6.1+cu122torch2.2.2cxx11abiFALSE-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
|
||||
https://github.com/Dao-AILab/flash-attention/releases/download/v2.6.1/flash_attn-2.6.1+cu123torch2.2cxx11abiFALSE-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
|
||||
https://github.com/Dao-AILab/flash-attention/releases/download/v2.6.1/flash_attn-2.6.1+cu123torch2.2cxx11abiFALSE-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
|
||||
autoawq==0.2.5; platform_system == "Linux" or platform_system == "Windows"
|
||||
|
||||
@ -1,10 +1,10 @@
|
||||
accelerate==0.30.*
|
||||
accelerate==0.32.*
|
||||
colorama
|
||||
datasets
|
||||
einops
|
||||
gradio==4.26.*
|
||||
hqq==0.1.7.post2
|
||||
jinja2==3.1.2
|
||||
hqq==0.1.7.post3
|
||||
jinja2==3.1.4
|
||||
lm_eval==0.3.0
|
||||
markdown
|
||||
numba==0.59.*
|
||||
@ -21,7 +21,7 @@ safetensors==0.4.*
|
||||
scipy
|
||||
sentencepiece
|
||||
tensorboard
|
||||
transformers==4.41.*
|
||||
transformers==4.42.*
|
||||
tqdm
|
||||
wandb
|
||||
|
||||
@ -32,16 +32,16 @@ sse-starlette==1.6.5
|
||||
tiktoken
|
||||
|
||||
# llama-cpp-python (CPU only, AVX2)
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.75+cpuavx2-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.75+cpuavx2-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.75+cpuavx2-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.75+cpuavx2-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.82+cpuavx2-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.82+cpuavx2-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.82+cpuavx2-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.82+cpuavx2-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
|
||||
|
||||
# AMD wheels
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/rocm/llama_cpp_python_cuda-0.2.75+rocm5.6.1-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/rocm/llama_cpp_python_cuda-0.2.75+rocm5.6.1-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
|
||||
https://github.com/oobabooga/exllamav2/releases/download/v0.0.20/exllamav2-0.0.20+rocm5.6-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
|
||||
https://github.com/oobabooga/exllamav2/releases/download/v0.0.20/exllamav2-0.0.20+rocm5.6-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
|
||||
https://github.com/oobabooga/exllamav2/releases/download/v0.0.20/exllamav2-0.0.20-py3-none-any.whl; platform_system != "Darwin" and platform_machine != "x86_64"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/rocm/llama_cpp_python_cuda-0.2.82+rocm5.6.1-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/rocm/llama_cpp_python_cuda-0.2.82+rocm5.6.1-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
|
||||
https://github.com/oobabooga/exllamav2/releases/download/v0.1.7/exllamav2-0.1.7+rocm5.6.torch2.2.2-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
|
||||
https://github.com/oobabooga/exllamav2/releases/download/v0.1.7/exllamav2-0.1.7+rocm5.6.torch2.2.2-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
|
||||
https://github.com/oobabooga/exllamav2/releases/download/v0.1.7/exllamav2-0.1.7-py3-none-any.whl; platform_system != "Darwin" and platform_machine != "x86_64"
|
||||
https://github.com/casper-hansen/AutoAWQ/releases/download/v0.2.5/autoawq-0.2.5+rocm561-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
|
||||
https://github.com/casper-hansen/AutoAWQ/releases/download/v0.2.5/autoawq-0.2.5+rocm561-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
|
||||
|
||||
@ -1,10 +1,10 @@
|
||||
accelerate==0.30.*
|
||||
accelerate==0.32.*
|
||||
colorama
|
||||
datasets
|
||||
einops
|
||||
gradio==4.26.*
|
||||
hqq==0.1.7.post2
|
||||
jinja2==3.1.2
|
||||
hqq==0.1.7.post3
|
||||
jinja2==3.1.4
|
||||
lm_eval==0.3.0
|
||||
markdown
|
||||
numba==0.59.*
|
||||
@ -21,7 +21,7 @@ safetensors==0.4.*
|
||||
scipy
|
||||
sentencepiece
|
||||
tensorboard
|
||||
transformers==4.41.*
|
||||
transformers==4.42.*
|
||||
tqdm
|
||||
wandb
|
||||
|
||||
@ -32,14 +32,14 @@ sse-starlette==1.6.5
|
||||
tiktoken
|
||||
|
||||
# llama-cpp-python (CPU only, no AVX2)
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.75+cpuavx-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.75+cpuavx-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.75+cpuavx-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.75+cpuavx-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.82+cpuavx-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.82+cpuavx-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.82+cpuavx-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.82+cpuavx-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
|
||||
|
||||
# AMD wheels
|
||||
https://github.com/oobabooga/exllamav2/releases/download/v0.0.20/exllamav2-0.0.20+rocm5.6-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
|
||||
https://github.com/oobabooga/exllamav2/releases/download/v0.0.20/exllamav2-0.0.20+rocm5.6-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
|
||||
https://github.com/oobabooga/exllamav2/releases/download/v0.0.20/exllamav2-0.0.20-py3-none-any.whl; platform_system != "Darwin" and platform_machine != "x86_64"
|
||||
https://github.com/oobabooga/exllamav2/releases/download/v0.1.7/exllamav2-0.1.7+rocm5.6.torch2.2.2-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
|
||||
https://github.com/oobabooga/exllamav2/releases/download/v0.1.7/exllamav2-0.1.7+rocm5.6.torch2.2.2-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
|
||||
https://github.com/oobabooga/exllamav2/releases/download/v0.1.7/exllamav2-0.1.7-py3-none-any.whl; platform_system != "Darwin" and platform_machine != "x86_64"
|
||||
https://github.com/casper-hansen/AutoAWQ/releases/download/v0.2.5/autoawq-0.2.5+rocm561-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
|
||||
https://github.com/casper-hansen/AutoAWQ/releases/download/v0.2.5/autoawq-0.2.5+rocm561-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
|
||||
|
||||
@ -1,10 +1,10 @@
|
||||
accelerate==0.30.*
|
||||
accelerate==0.32.*
|
||||
colorama
|
||||
datasets
|
||||
einops
|
||||
gradio==4.26.*
|
||||
hqq==0.1.7.post2
|
||||
jinja2==3.1.2
|
||||
hqq==0.1.7.post3
|
||||
jinja2==3.1.4
|
||||
lm_eval==0.3.0
|
||||
markdown
|
||||
numba==0.59.*
|
||||
@ -21,7 +21,7 @@ safetensors==0.4.*
|
||||
scipy
|
||||
sentencepiece
|
||||
tensorboard
|
||||
transformers==4.41.*
|
||||
transformers==4.42.*
|
||||
tqdm
|
||||
wandb
|
||||
|
||||
@ -32,10 +32,8 @@ sse-starlette==1.6.5
|
||||
tiktoken
|
||||
|
||||
# Mac wheels
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/metal/llama_cpp_python-0.2.75-cp311-cp311-macosx_11_0_x86_64.whl; platform_system == "Darwin" and platform_release >= "20.0.0" and platform_release < "21.0.0" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/metal/llama_cpp_python-0.2.75-cp310-cp310-macosx_11_0_x86_64.whl; platform_system == "Darwin" and platform_release >= "20.0.0" and platform_release < "21.0.0" and python_version == "3.10"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/metal/llama_cpp_python-0.2.75-cp311-cp311-macosx_12_0_x86_64.whl; platform_system == "Darwin" and platform_release >= "21.0.0" and platform_release < "22.0.0" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/metal/llama_cpp_python-0.2.75-cp310-cp310-macosx_12_0_x86_64.whl; platform_system == "Darwin" and platform_release >= "21.0.0" and platform_release < "22.0.0" and python_version == "3.10"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/metal/llama_cpp_python-0.2.75-cp311-cp311-macosx_14_0_x86_64.whl; platform_system == "Darwin" and platform_release >= "23.0.0" and platform_release < "24.0.0" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/metal/llama_cpp_python-0.2.75-cp310-cp310-macosx_14_0_x86_64.whl; platform_system == "Darwin" and platform_release >= "23.0.0" and platform_release < "24.0.0" and python_version == "3.10"
|
||||
https://github.com/oobabooga/exllamav2/releases/download/v0.0.20/exllamav2-0.0.20-py3-none-any.whl
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/metal/llama_cpp_python-0.2.82-cp311-cp311-macosx_12_0_x86_64.whl; platform_system == "Darwin" and platform_release >= "21.0.0" and platform_release < "22.0.0" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/metal/llama_cpp_python-0.2.82-cp310-cp310-macosx_12_0_x86_64.whl; platform_system == "Darwin" and platform_release >= "21.0.0" and platform_release < "22.0.0" and python_version == "3.10"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/metal/llama_cpp_python-0.2.82-cp311-cp311-macosx_14_0_x86_64.whl; platform_system == "Darwin" and platform_release >= "23.0.0" and platform_release < "24.0.0" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/metal/llama_cpp_python-0.2.82-cp310-cp310-macosx_14_0_x86_64.whl; platform_system == "Darwin" and platform_release >= "23.0.0" and platform_release < "24.0.0" and python_version == "3.10"
|
||||
https://github.com/oobabooga/exllamav2/releases/download/v0.1.7/exllamav2-0.1.7-py3-none-any.whl
|
||||
|
||||
@ -1,10 +1,10 @@
|
||||
accelerate==0.30.*
|
||||
accelerate==0.32.*
|
||||
colorama
|
||||
datasets
|
||||
einops
|
||||
gradio==4.26.*
|
||||
hqq==0.1.7.post2
|
||||
jinja2==3.1.2
|
||||
hqq==0.1.7.post3
|
||||
jinja2==3.1.4
|
||||
lm_eval==0.3.0
|
||||
markdown
|
||||
numba==0.59.*
|
||||
@ -21,7 +21,7 @@ safetensors==0.4.*
|
||||
scipy
|
||||
sentencepiece
|
||||
tensorboard
|
||||
transformers==4.41.*
|
||||
transformers==4.42.*
|
||||
tqdm
|
||||
wandb
|
||||
|
||||
@ -32,12 +32,10 @@ sse-starlette==1.6.5
|
||||
tiktoken
|
||||
|
||||
# Mac wheels
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/metal/llama_cpp_python-0.2.75-cp311-cp311-macosx_11_0_arm64.whl; platform_system == "Darwin" and platform_release >= "20.0.0" and platform_release < "21.0.0" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/metal/llama_cpp_python-0.2.75-cp310-cp310-macosx_11_0_arm64.whl; platform_system == "Darwin" and platform_release >= "20.0.0" and platform_release < "21.0.0" and python_version == "3.10"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/metal/llama_cpp_python-0.2.75-cp311-cp311-macosx_12_0_arm64.whl; platform_system == "Darwin" and platform_release >= "21.0.0" and platform_release < "22.0.0" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/metal/llama_cpp_python-0.2.75-cp310-cp310-macosx_12_0_arm64.whl; platform_system == "Darwin" and platform_release >= "21.0.0" and platform_release < "22.0.0" and python_version == "3.10"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/metal/llama_cpp_python-0.2.75-cp311-cp311-macosx_13_0_arm64.whl; platform_system == "Darwin" and platform_release >= "22.0.0" and platform_release < "23.0.0" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/metal/llama_cpp_python-0.2.75-cp310-cp310-macosx_13_0_arm64.whl; platform_system == "Darwin" and platform_release >= "22.0.0" and platform_release < "23.0.0" and python_version == "3.10"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/metal/llama_cpp_python-0.2.75-cp311-cp311-macosx_14_0_arm64.whl; platform_system == "Darwin" and platform_release >= "23.0.0" and platform_release < "24.0.0" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/metal/llama_cpp_python-0.2.75-cp310-cp310-macosx_14_0_arm64.whl; platform_system == "Darwin" and platform_release >= "23.0.0" and platform_release < "24.0.0" and python_version == "3.10"
|
||||
https://github.com/oobabooga/exllamav2/releases/download/v0.0.20/exllamav2-0.0.20-py3-none-any.whl
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/metal/llama_cpp_python-0.2.82-cp311-cp311-macosx_12_0_arm64.whl; platform_system == "Darwin" and platform_release >= "21.0.0" and platform_release < "22.0.0" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/metal/llama_cpp_python-0.2.82-cp310-cp310-macosx_12_0_arm64.whl; platform_system == "Darwin" and platform_release >= "21.0.0" and platform_release < "22.0.0" and python_version == "3.10"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/metal/llama_cpp_python-0.2.82-cp311-cp311-macosx_13_0_arm64.whl; platform_system == "Darwin" and platform_release >= "22.0.0" and platform_release < "23.0.0" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/metal/llama_cpp_python-0.2.82-cp310-cp310-macosx_13_0_arm64.whl; platform_system == "Darwin" and platform_release >= "22.0.0" and platform_release < "23.0.0" and python_version == "3.10"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/metal/llama_cpp_python-0.2.82-cp311-cp311-macosx_14_0_arm64.whl; platform_system == "Darwin" and platform_release >= "23.0.0" and platform_release < "24.0.0" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/metal/llama_cpp_python-0.2.82-cp310-cp310-macosx_14_0_arm64.whl; platform_system == "Darwin" and platform_release >= "23.0.0" and platform_release < "24.0.0" and python_version == "3.10"
|
||||
https://github.com/oobabooga/exllamav2/releases/download/v0.1.7/exllamav2-0.1.7-py3-none-any.whl
|
||||
|
||||
@ -1,10 +1,10 @@
|
||||
accelerate==0.30.*
|
||||
accelerate==0.32.*
|
||||
colorama
|
||||
datasets
|
||||
einops
|
||||
gradio==4.26.*
|
||||
hqq==0.1.7.post2
|
||||
jinja2==3.1.2
|
||||
hqq==0.1.7.post3
|
||||
jinja2==3.1.4
|
||||
lm_eval==0.3.0
|
||||
markdown
|
||||
numba==0.59.*
|
||||
@ -21,7 +21,7 @@ safetensors==0.4.*
|
||||
scipy
|
||||
sentencepiece
|
||||
tensorboard
|
||||
transformers==4.41.*
|
||||
transformers==4.42.*
|
||||
tqdm
|
||||
wandb
|
||||
|
||||
@ -32,7 +32,7 @@ sse-starlette==1.6.5
|
||||
tiktoken
|
||||
|
||||
# llama-cpp-python (CPU only, AVX2)
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.75+cpuavx2-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.75+cpuavx2-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.75+cpuavx2-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.75+cpuavx2-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.82+cpuavx2-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.82+cpuavx2-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.82+cpuavx2-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.82+cpuavx2-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
|
||||
|
||||
@ -1,10 +1,10 @@
|
||||
accelerate==0.30.*
|
||||
accelerate==0.32.*
|
||||
colorama
|
||||
datasets
|
||||
einops
|
||||
gradio==4.26.*
|
||||
hqq==0.1.7.post2
|
||||
jinja2==3.1.2
|
||||
hqq==0.1.7.post3
|
||||
jinja2==3.1.4
|
||||
lm_eval==0.3.0
|
||||
markdown
|
||||
numba==0.59.*
|
||||
@ -21,7 +21,7 @@ safetensors==0.4.*
|
||||
scipy
|
||||
sentencepiece
|
||||
tensorboard
|
||||
transformers==4.41.*
|
||||
transformers==4.42.*
|
||||
tqdm
|
||||
wandb
|
||||
|
||||
@ -32,7 +32,7 @@ sse-starlette==1.6.5
|
||||
tiktoken
|
||||
|
||||
# llama-cpp-python (CPU only, no AVX2)
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.75+cpuavx-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.75+cpuavx-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.75+cpuavx-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.75+cpuavx-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.82+cpuavx-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.82+cpuavx-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.82+cpuavx-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.82+cpuavx-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
|
||||
|
||||
@ -1,13 +1,13 @@
|
||||
accelerate==0.30.*
|
||||
aqlm[gpu,cpu]==1.1.5; platform_system == "Linux"
|
||||
accelerate==0.32.*
|
||||
aqlm[gpu,cpu]==1.1.6; platform_system == "Linux"
|
||||
auto-gptq==0.7.1
|
||||
bitsandbytes==0.43.*
|
||||
colorama
|
||||
datasets
|
||||
einops
|
||||
gradio==4.26.*
|
||||
hqq==0.1.7.post2
|
||||
jinja2==3.1.2
|
||||
hqq==0.1.7.post3
|
||||
jinja2==3.1.4
|
||||
lm_eval==0.3.0
|
||||
markdown
|
||||
numba==0.59.*
|
||||
@ -24,7 +24,7 @@ safetensors==0.4.*
|
||||
scipy
|
||||
sentencepiece
|
||||
tensorboard
|
||||
transformers==4.41.*
|
||||
transformers==4.42.*
|
||||
tqdm
|
||||
wandb
|
||||
|
||||
@ -35,31 +35,31 @@ sse-starlette==1.6.5
|
||||
tiktoken
|
||||
|
||||
# llama-cpp-python (CPU only, no AVX2)
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.75+cpuavx-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.75+cpuavx-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.75+cpuavx-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.75+cpuavx-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.82+cpuavx-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.82+cpuavx-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.82+cpuavx-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/cpu/llama_cpp_python-0.2.82+cpuavx-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
|
||||
|
||||
# llama-cpp-python (CUDA, no tensor cores)
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/textgen-webui/llama_cpp_python_cuda-0.2.75+cu121avx-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/textgen-webui/llama_cpp_python_cuda-0.2.75+cu121avx-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/textgen-webui/llama_cpp_python_cuda-0.2.75+cu121avx-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/textgen-webui/llama_cpp_python_cuda-0.2.75+cu121avx-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/textgen-webui/llama_cpp_python_cuda-0.2.82+cu121avx-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/textgen-webui/llama_cpp_python_cuda-0.2.82+cu121avx-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/textgen-webui/llama_cpp_python_cuda-0.2.82+cu121avx-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/textgen-webui/llama_cpp_python_cuda-0.2.82+cu121avx-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
|
||||
|
||||
# llama-cpp-python (CUDA, tensor cores)
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/textgen-webui/llama_cpp_python_cuda_tensorcores-0.2.75+cu121avx-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/textgen-webui/llama_cpp_python_cuda_tensorcores-0.2.75+cu121avx-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/textgen-webui/llama_cpp_python_cuda_tensorcores-0.2.75+cu121avx-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/textgen-webui/llama_cpp_python_cuda_tensorcores-0.2.75+cu121avx-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/textgen-webui/llama_cpp_python_cuda_tensorcores-0.2.82+cu121avx-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/textgen-webui/llama_cpp_python_cuda_tensorcores-0.2.82+cu121avx-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/textgen-webui/llama_cpp_python_cuda_tensorcores-0.2.82+cu121avx-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
|
||||
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/textgen-webui/llama_cpp_python_cuda_tensorcores-0.2.82+cu121avx-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
|
||||
|
||||
# CUDA wheels
|
||||
https://github.com/oobabooga/exllamav2/releases/download/v0.0.20/exllamav2-0.0.20+cu121-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
|
||||
https://github.com/oobabooga/exllamav2/releases/download/v0.0.20/exllamav2-0.0.20+cu121-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
|
||||
https://github.com/oobabooga/exllamav2/releases/download/v0.0.20/exllamav2-0.0.20+cu121-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
|
||||
https://github.com/oobabooga/exllamav2/releases/download/v0.0.20/exllamav2-0.0.20+cu121-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
|
||||
https://github.com/oobabooga/exllamav2/releases/download/v0.0.20/exllamav2-0.0.20-py3-none-any.whl; platform_system == "Linux" and platform_machine != "x86_64"
|
||||
https://github.com/oobabooga/flash-attention/releases/download/v2.5.6/flash_attn-2.5.6+cu122torch2.2.0cxx11abiFALSE-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
|
||||
https://github.com/oobabooga/flash-attention/releases/download/v2.5.6/flash_attn-2.5.6+cu122torch2.2.0cxx11abiFALSE-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
|
||||
https://github.com/Dao-AILab/flash-attention/releases/download/v2.5.6/flash_attn-2.5.6+cu122torch2.2cxx11abiFALSE-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
|
||||
https://github.com/Dao-AILab/flash-attention/releases/download/v2.5.6/flash_attn-2.5.6+cu122torch2.2cxx11abiFALSE-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
|
||||
https://github.com/oobabooga/exllamav2/releases/download/v0.1.7/exllamav2-0.1.7+cu121.torch2.2.2-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
|
||||
https://github.com/oobabooga/exllamav2/releases/download/v0.1.7/exllamav2-0.1.7+cu121.torch2.2.2-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
|
||||
https://github.com/oobabooga/exllamav2/releases/download/v0.1.7/exllamav2-0.1.7+cu121.torch2.2.2-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
|
||||
https://github.com/oobabooga/exllamav2/releases/download/v0.1.7/exllamav2-0.1.7+cu121.torch2.2.2-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
|
||||
https://github.com/oobabooga/exllamav2/releases/download/v0.1.7/exllamav2-0.1.7-py3-none-any.whl; platform_system == "Linux" and platform_machine != "x86_64"
|
||||
https://github.com/oobabooga/flash-attention/releases/download/v2.6.1/flash_attn-2.6.1+cu122torch2.2.2cxx11abiFALSE-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
|
||||
https://github.com/oobabooga/flash-attention/releases/download/v2.6.1/flash_attn-2.6.1+cu122torch2.2.2cxx11abiFALSE-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
|
||||
https://github.com/Dao-AILab/flash-attention/releases/download/v2.6.1/flash_attn-2.6.1+cu123torch2.2cxx11abiFALSE-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
|
||||
https://github.com/Dao-AILab/flash-attention/releases/download/v2.6.1/flash_attn-2.6.1+cu123torch2.2cxx11abiFALSE-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
|
||||
autoawq==0.2.5; platform_system == "Linux" or platform_system == "Windows"
|
||||
|
||||
@ -1,10 +1,10 @@
|
||||
accelerate==0.30.*
|
||||
accelerate==0.32.*
|
||||
colorama
|
||||
datasets
|
||||
einops
|
||||
gradio==4.26.*
|
||||
hqq==0.1.7.post2
|
||||
jinja2==3.1.2
|
||||
hqq==0.1.7.post3
|
||||
jinja2==3.1.4
|
||||
lm_eval==0.3.0
|
||||
markdown
|
||||
numba==0.59.*
|
||||
@ -21,7 +21,7 @@ safetensors==0.4.*
|
||||
scipy
|
||||
sentencepiece
|
||||
tensorboard
|
||||
transformers==4.41.*
|
||||
transformers==4.42.*
|
||||
tqdm
|
||||
wandb
|
||||
|
||||
|
||||
@ -146,9 +146,9 @@ def create_interface():
|
||||
ui_model_menu.create_event_handlers()
|
||||
|
||||
# Interface launch events
|
||||
shared.gradio['interface'].load(lambda: None, None, None, js=f"() => {{if ({str(shared.settings['dark_theme']).lower()}) {{ document.getElementsByTagName('body')[0].classList.add('dark'); }} }}")
|
||||
shared.gradio['interface'].load(lambda: None, None, None, js=f"() => {{{js}}}")
|
||||
shared.gradio['interface'].load(lambda x: None, gradio('show_controls'), None, js=f'(x) => {{{ui.show_controls_js}; toggle_controls(x)}}')
|
||||
shared.gradio['interface'].load(None, None, None, js=f"() => {{if ({str(shared.settings['dark_theme']).lower()}) {{ document.getElementsByTagName('body')[0].classList.add('dark'); }} }}")
|
||||
shared.gradio['interface'].load(None, None, None, js=f"() => {{{js}}}")
|
||||
shared.gradio['interface'].load(None, gradio('show_controls'), None, js=f'(x) => {{{ui.show_controls_js}; toggle_controls(x)}}')
|
||||
shared.gradio['interface'].load(partial(ui.apply_interface_values, {}, use_persistent=True), None, gradio(ui.list_interface_input_elements()), show_progress=False)
|
||||
shared.gradio['interface'].load(chat.redraw_html, gradio(ui_chat.reload_arr), gradio('display'))
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user