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48
README.md
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@ -10,33 +10,29 @@ Its goal is to become the [AUTOMATIC1111/stable-diffusion-webui](https://github.
## Features
* Multiple backends for text generation in a single UI and API, including [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), and [TensorRT-LLM](https://github.com/NVIDIA/TensorRT-LLM). [AutoAWQ](https://github.com/casper-hansen/AutoAWQ), [HQQ](https://github.com/mobiusml/hqq), and [AQLM](https://github.com/Vahe1994/AQLM) are also supported through the Transformers loader.
* OpenAI-compatible API server with Chat and Completions endpoints – see the [examples](https://github.com/oobabooga/text-generation-webui/wiki/12-%E2%80%90-OpenAI-API#examples).
* Automatic prompt formatting for each model using the Jinja2 template in its metadata.
* Three chat modes: `instruct`, `chat-instruct`, and `chat`, allowing for both instruction-following and casual conversations with characters. `chat-instruct` mode automatically applies the model's template to the chat prompt, ensuring high-quality outputs without manual setup.
* "Past chats" menu to quickly switch between conversations and start new ones.
* Free-form generation in the Default/Notebook tabs without being limited to chat turns. Send formatted chat conversations from the Chat tab to these tabs.
* Multiple sampling parameters and generation options for sophisticated text generation control.
* Easy switching between different models through the UI without restarting, using the "Model" tab.
* Simple LoRA fine-tuning tool to customize models with your data.
* All in one folder. The requirements are installed in a self-contained `installer_files` folder that doesn't interfere with the system's environment.
* Extensions support, including numerous built-in and user-contributed extensions. 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.
- Supports multiple text generation backends in one UI/API, including [Transformers](https://github.com/huggingface/transformers), [llama.cpp](https://github.com/ggerganov/llama.cpp), and [ExLlamaV2](https://github.com/turboderp/exllamav2). [TensorRT-LLM](https://github.com/NVIDIA/TensorRT-LLM), [AutoGPTQ](https://github.com/PanQiWei/AutoGPTQ), [AutoAWQ](https://github.com/casper-hansen/AutoAWQ), [HQQ](https://github.com/mobiusml/hqq), and [AQLM](https://github.com/Vahe1994/AQLM) are also supported but you need to install them manually.
- OpenAI-compatible API with Chat and Completions endpoints – see [examples](https://github.com/oobabooga/text-generation-webui/wiki/12-%E2%80%90-OpenAI-API#examples).
- Automatic prompt formatting using Jinja2 templates.
- Three chat modes: `instruct`, `chat-instruct`, and `chat`, with automatic prompt templates in `chat-instruct`.
- "Past chats" menu to quickly switch between conversations.
- Free-form text generation in the Default/Notebook tabs without being limited to chat turns. You can send formatted conversations from the Chat tab to these.
- Multiple sampling parameters and generation options for sophisticated text generation control.
- Switch between different models easily in the UI without restarting.
- Simple LoRA fine-tuning tool.
- Requirements installed in a self-contained `installer_files` directory that doesn't interfere with the system environment.
- Extension support, with numerous built-in and user-contributed extensions available. See the [wiki](https://github.com/oobabooga/text-generation-webui/wiki/07-%E2%80%90-Extensions) and [extensions directory](https://github.com/oobabooga/text-generation-webui-extensions) for details.
## How to install
1) Clone or [download](https://github.com/oobabooga/text-generation-webui/archive/refs/heads/main.zip) the repository.
2) Run the `start_linux.sh`, `start_windows.bat`, `start_macos.sh`, or `start_wsl.bat` script depending on your OS.
1) Clone or [download the repository](https://github.com/oobabooga/text-generation-webui/archive/refs/heads/main.zip).
2) Run the script that matches your OS: `start_linux.sh`, `start_windows.bat`, `start_macos.sh`, or `start_wsl.bat`.
3) Select your GPU vendor when asked.
4) Once the installation ends, browse to `http://localhost:7860`.
5) Have fun!
To restart the web UI in the future, run the `start_` script again.
To restart the web UI later, just run the same `start_` script. If you need to reinstall, delete the `installer_files` folder created during setup and run the script again.
This script creates an `installer_files` folder where it sets up the project's requirements. If you need to reinstall the requirements, just delete that folder and start the web UI again.
The script accepts command-line flags, such as `./start_linux.sh --help`. Alternatively, you can edit the `CMD_FLAGS.txt` file with a text editor and add your flags there, such as `--api` in case you need to use the API.
To get updates in the future, run `update_wizard_linux.sh`, `update_wizard_windows.bat`, `update_wizard_macos.sh`, or `update_wizard_wsl.bat`.
You can use command-line flags, like `./start_linux.sh --help`, or add them to `CMD_FLAGS.txt` (such as `--api` to enable API use). To update the project, run `update_wizard_linux.sh`, `update_wizard_windows.bat`, `update_wizard_macos.sh`, or `update_wizard_wsl.bat`.
<details>
<summary>
@ -80,12 +76,12 @@ conda activate textgen
| System | GPU | Command |
|--------|---------|---------|
| 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` |
| Linux/WSL | NVIDIA | `pip3 install torch==2.4.1 torchvision==0.19.1 torchaudio==2.4.1 --index-url https://download.pytorch.org/whl/cu121` |
| Linux/WSL | CPU only | `pip3 install torch==2.4.1 torchvision==0.19.1 torchaudio==2.4.1 --index-url https://download.pytorch.org/whl/cpu` |
| Linux | AMD | `pip3 install torch==2.4.1 torchvision==0.19.1 torchaudio==2.4.1 --index-url https://download.pytorch.org/whl/rocm6.1` |
| MacOS + MPS | Any | `pip3 install torch==2.4.1 torchvision==0.19.1 torchaudio==2.4.1` |
| Windows | NVIDIA | `pip3 install torch==2.4.1 torchvision==0.19.1 torchaudio==2.4.1 --index-url https://download.pytorch.org/whl/cu121` |
| Windows | CPU only | `pip3 install torch==2.4.1 torchvision==0.19.1 torchaudio==2.4.1` |
The up-to-date commands can be found here: https://pytorch.org/get-started/locally/.
@ -150,7 +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==2.2.2 torchvision==0.17.2 torchaudio==2.2.2 --index-url https://download.pytorch.org/whl/cu118
pip3 install torch==2.4.1 torchvision==0.19.1 torchaudio==2.4.1 --index-url https://download.pytorch.org/whl/cu118
conda install -y -c "nvidia/label/cuda-11.8.0" cuda-runtime
```

26
docs/12 - OpenAI API.md
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@ -19,7 +19,7 @@ Add `--api` to your command-line flags.
### Examples
For the documentation with all the parameters and their types, consult `http://127.0.0.1:5000/docs` or the [typing.py](https://github.com/oobabooga/text-generation-webui/blob/main/extensions/openai/typing.py) file.
For the documentation with all the endpoints, parameters and their types, consult `http://127.0.0.1:5000/docs` or the [typing.py](https://github.com/oobabooga/text-generation-webui/blob/main/extensions/openai/typing.py) file.
The official examples in the [OpenAI documentation](https://platform.openai.com/docs/api-reference) should also work, and the same parameters apply (although the API here has more optional parameters).
@ -114,6 +114,30 @@ curl -k http://127.0.0.1:5000/v1/internal/logits \
}'
```
#### List models
```shell
curl -k http://127.0.0.1:5000/v1/internal/model/list \
-H "Content-Type: application/json"
```
#### Load model
```shell
curl -k http://127.0.0.1:5000/v1/internal/model/load \
-H "Content-Type: application/json" \
-d '{
"model_name": "model_name",
"args": {
"load_in_4bit": true,
"n_gpu_layers": 12
},
"settings": {
"instruction_template": "Alpaca"
}
}'
```
#### Python chat example
```python

2
extensions/Training_PRO/script.py
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@ -241,7 +241,7 @@ def ui():
stride_length = gr.Slider(label='Stride', minimum=1, maximum=2048, value=512, step=1, info='Used to make the evaluation faster at the cost of accuracy. 1 = slowest but most accurate. 512 is a common value.')
with gr.Column():
max_length = gr.Slider(label='max_length', minimum=0, maximum=shared.settings['truncation_length_max'], value=0, step=1, info='The context for each evaluation. If set to 0, the maximum context length for the model will be used.')
max_length = gr.Number(label='max_length', precision=0, step=256, value=0, info='The context for each evaluation. If set to 0, the maximum context length for the model will be used.')
with gr.Row():
start_current_evaluation = gr.Button("Evaluate loaded model")

5
extensions/openai/completions.py
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@ -154,8 +154,9 @@ def convert_history(history):
elif item['type'] == 'text' and isinstance(item['text'], str):
content = item['text']
if image_url and content:
if image_url:
new_history.append({"image_url": image_url, "role": "user"})
if content:
new_history.append({"content": content, "role": "user"})
else:
new_history.append(entry)
@ -234,7 +235,7 @@ def chat_completions_common(body: dict, is_legacy: bool = False, stream=False, p
raise InvalidRequestError(message="messages: missing content", param='messages')
# Chat Completions
object_type = 'chat.completions' if not stream else 'chat.completions.chunk'
object_type = 'chat.completion' if not stream else 'chat.completion.chunk'
created_time = int(time.time())
cmpl_id = "chatcmpl-%d" % (int(time.time() * 1000000000))
resp_list = 'data' if is_legacy else 'choices'

2
extensions/openai/typing.py
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@ -37,6 +37,8 @@ class GenerationOptions(BaseModel):
dry_base: float = 1.75
dry_allowed_length: int = 2
dry_sequence_breakers: str = '"\\n", ":", "\\"", "*"'
xtc_threshold: float = 0.1
xtc_probability: float = 0
truncation_length: int = 0
max_tokens_second: int = 0
prompt_lookup_num_tokens: int = 0

11
js/main.js
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@ -600,4 +600,15 @@ headerBar.addEventListener("click", (e) => {
}
});
//------------------------------------------------
// Add a confirmation dialog when leaving the page
// Useful to avoid data loss
//------------------------------------------------
window.addEventListener("beforeunload", function (event) {
// Cancel the event
event.preventDefault();
// Chrome requires returnValue to be set
event.returnValue = "";
});
moveToChatTab();

4
modules/LoRA.py
View File

@ -1,7 +1,6 @@
from pathlib import Path
import torch
from peft import PeftModel
from transformers import is_torch_xpu_available
import modules.shared as shared
@ -85,6 +84,9 @@ def add_lora_autogptq(lora_names):
def add_lora_transformers(lora_names):
from peft import PeftModel
prior_set = set(shared.lora_names)
added_set = set(lora_names) - prior_set
removed_set = prior_set - set(lora_names)

28
modules/chat.py
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@ -1059,7 +1059,12 @@ def handle_start_new_chat_click(state):
convert_to_markdown.cache_clear()
return [history, html, gr.update(choices=histories, value=histories[0][1])]
if len(histories) > 0:
past_chats_update = gr.update(choices=histories, value=histories[0][1])
else:
past_chats_update = gr.update(choices=histories)
return [history, html, past_chats_update]
def handle_delete_chat_confirm_click(state):
@ -1110,10 +1115,15 @@ def handle_upload_chat_history(load_chat_history, state):
convert_to_markdown.cache_clear()
if len(histories) > 0:
past_chats_update = gr.update(choices=histories, value=histories[0][1])
else:
past_chats_update = gr.update(choices=histories)
return [
history,
html,
gr.update(choices=histories, value=histories[0][1])
past_chats_update
]
@ -1132,6 +1142,11 @@ def handle_character_menu_change(state):
convert_to_markdown.cache_clear()
if len(histories) > 0:
past_chats_update = gr.update(choices=histories, value=histories[0][1])
else:
past_chats_update = gr.update(choices=histories)
return [
history,
html,
@ -1140,7 +1155,7 @@ def handle_character_menu_change(state):
picture,
greeting,
context,
gr.update(choices=histories, value=histories[0][1]),
past_chats_update,
]
@ -1151,12 +1166,17 @@ def handle_mode_change(state):
convert_to_markdown.cache_clear()
if len(histories) > 0:
past_chats_update = gr.update(choices=histories, value=histories[0][1])
else:
past_chats_update = gr.update(choices=histories)
return [
history,
html,
gr.update(visible=state['mode'] != 'instruct'),
gr.update(visible=state['mode'] == 'chat-instruct'),
gr.update(choices=histories, value=histories[0][1])
past_chats_update
]

34
modules/exllamav2.py
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@ -7,6 +7,7 @@ from exllamav2 import (
ExLlamaV2Cache,
ExLlamaV2Cache_8bit,
ExLlamaV2Cache_Q4,
ExLlamaV2Cache_TP,
ExLlamaV2Config,
ExLlamaV2Tokenizer
)
@ -18,14 +19,6 @@ from modules.text_generation import get_max_prompt_length
try:
import flash_attn
except ModuleNotFoundError:
logger.warning(
'You are running ExLlamaV2 without flash-attention. This will cause the VRAM usage '
'to be a lot higher than it could be.\n'
'Try installing flash-attention following the instructions here: '
'https://github.com/Dao-AILab/flash-attention#installation-and-features'
)
pass
except Exception:
logger.warning('Failed to load flash-attention due to the following error:\n')
traceback.print_exc()
@ -54,21 +47,30 @@ class Exllamav2Model:
model = ExLlamaV2(config)
if not shared.args.autosplit:
split = None
if shared.args.gpu_split:
split = [float(alloc) for alloc in shared.args.gpu_split.split(",")]
split = None
if shared.args.gpu_split:
split = [float(alloc) for alloc in shared.args.gpu_split.split(",")]
if shared.args.enable_tp:
model.load_tp(split)
elif not shared.args.autosplit:
model.load(split)
# Determine the correct cache type
if shared.args.cache_8bit:
cache = ExLlamaV2Cache_8bit(model, lazy=shared.args.autosplit)
cache_type = ExLlamaV2Cache_8bit
elif shared.args.cache_4bit:
cache = ExLlamaV2Cache_Q4(model, lazy=shared.args.autosplit)
cache_type = ExLlamaV2Cache_Q4
else:
cache = ExLlamaV2Cache(model, lazy=shared.args.autosplit)
cache_type = ExLlamaV2Cache
if shared.args.autosplit:
# Use TP if specified
if shared.args.enable_tp:
cache = ExLlamaV2Cache_TP(model, base=cache_type)
else:
cache = cache_type(model, lazy=shared.args.autosplit)
if shared.args.autosplit and not shared.args.enable_tp:
model.load_autosplit(cache)
tokenizer = ExLlamaV2Tokenizer(config)

34
modules/exllamav2_hf.py
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@ -9,6 +9,7 @@ from exllamav2 import (
ExLlamaV2Cache,
ExLlamaV2Cache_8bit,
ExLlamaV2Cache_Q4,
ExLlamaV2Cache_TP,
ExLlamaV2Config
)
from torch.nn import CrossEntropyLoss
@ -20,14 +21,6 @@ from modules.logging_colors import logger
try:
import flash_attn
except ModuleNotFoundError:
logger.warning(
'You are running ExLlamaV2 without flash-attention. This will cause the VRAM usage '
'to be a lot higher than it could be.\n'
'Try installing flash-attention following the instructions here: '
'https://github.com/Dao-AILab/flash-attention#installation-and-features'
)
pass
except Exception:
logger.warning('Failed to load flash-attention due to the following error:\n')
traceback.print_exc()
@ -42,21 +35,30 @@ class Exllamav2HF(PreTrainedModel):
self.ex_model = ExLlamaV2(config)
if not shared.args.autosplit:
split = None
if shared.args.gpu_split:
split = [float(alloc) for alloc in shared.args.gpu_split.split(",")]
split = None
if shared.args.gpu_split:
split = [float(alloc) for alloc in shared.args.gpu_split.split(",")]
if shared.args.enable_tp:
self.ex_model.load_tp(split)
elif not shared.args.autosplit:
self.ex_model.load(split)
# Determine the correct cache type
if shared.args.cache_8bit:
self.ex_cache = ExLlamaV2Cache_8bit(self.ex_model, lazy=shared.args.autosplit)
cache_type = ExLlamaV2Cache_8bit
elif shared.args.cache_4bit:
self.ex_cache = ExLlamaV2Cache_Q4(self.ex_model, lazy=shared.args.autosplit)
cache_type = ExLlamaV2Cache_Q4
else:
self.ex_cache = ExLlamaV2Cache(self.ex_model, lazy=shared.args.autosplit)
cache_type = ExLlamaV2Cache
if shared.args.autosplit:
# Use TP if specified
if shared.args.enable_tp:
self.ex_cache = ExLlamaV2Cache_TP(self.ex_model, base=cache_type)
else:
self.ex_cache = cache_type(self.ex_model, lazy=shared.args.autosplit)
if shared.args.autosplit and not shared.args.enable_tp:
self.ex_model.load_autosplit(self.ex_cache)
self.past_seq = None

21
modules/llama_cpp_python_hijack.py
View File

@ -2,12 +2,12 @@ import importlib
import platform
from typing import Sequence
import numpy as np
from tqdm import tqdm
from modules import shared
from modules.cache_utils import process_llamacpp_cache
imported_module = None
@ -57,11 +57,9 @@ def eval_with_progress(self, tokens: Sequence[int]):
with tqdm to show prompt processing progress.
"""
assert self._ctx.ctx is not None
assert self._batch.batch is not None
self._ctx.kv_cache_seq_rm(-1, self.n_tokens, -1)
if len(tokens) > 1:
if len(tokens) > self.n_batch:
progress_bar = tqdm(range(0, len(tokens), self.n_batch), desc="Prompt evaluation", leave=False)
else:
progress_bar = range(0, len(tokens), self.n_batch)
@ -80,13 +78,20 @@ def eval_with_progress(self, tokens: Sequence[int]):
if self.context_params.logits_all:
rows = n_tokens
cols = self._n_vocab
logits = self._ctx.get_logits()[: rows * cols]
self.scores[n_past : n_past + n_tokens, :].reshape(-1)[: :] = logits
logits = np.ctypeslib.as_array(
self._ctx.get_logits(), shape=(rows * cols,)
)
self.scores[n_past : n_past + n_tokens, :].reshape(-1)[::] = logits
self.last_updated_index = n_past + n_tokens - 1
else:
rows = 1
cols = self._n_vocab
logits = self._ctx.get_logits()[: rows * cols]
self.scores[n_past + n_tokens - 1, :].reshape(-1)[: :] = logits
logits = np.ctypeslib.as_array(
self._ctx.get_logits(), shape=(rows * cols,)
)
last_token_index = min(n_past + n_tokens - 1, self.scores.shape[0] - 1)
self.scores[last_token_index, :] = logits.reshape(-1)
self.last_updated_index = last_token_index
# Update n_tokens
self.n_tokens += n_tokens

3
modules/llamacpp_hf.py
View File

@ -127,7 +127,7 @@ class LlamacppHF(PreTrainedModel):
self.model.reset()
self.model.eval(seq)
logits = torch.tensor(self.model.scores[self.model.n_tokens - 1, :]).view(1, 1, -1).to(input_ids.device)
logits = torch.tensor(self.model.scores[self.model.last_updated_index, :]).view(1, 1, -1).to(input_ids.device)
else:
self.model.reset()
self.model.eval(seq)
@ -205,5 +205,6 @@ class LlamacppHF(PreTrainedModel):
Llama = llama_cpp_lib().Llama
model = Llama(**params)
model.last_updated_index = -1
return LlamacppHF(model, model_file)

8
modules/loaders.py
View File

@ -90,6 +90,7 @@ loaders_and_params = OrderedDict({
'cache_8bit',
'cache_4bit',
'autosplit',
'enable_tp',
'alpha_value',
'compress_pos_emb',
'trust_remote_code',
@ -105,6 +106,7 @@ loaders_and_params = OrderedDict({
'cache_8bit',
'cache_4bit',
'autosplit',
'enable_tp',
'alpha_value',
'compress_pos_emb',
'exllamav2_info',
@ -168,6 +170,8 @@ def transformers_samplers():
'dry_base',
'dry_allowed_length',
'dry_sequence_breakers',
'xtc_threshold',
'xtc_probability',
'seed',
'do_sample',
'penalty_alpha',
@ -242,6 +246,8 @@ loaders_samplers = {
'dry_base',
'dry_allowed_length',
'dry_sequence_breakers',
'xtc_threshold',
'xtc_probability',
'seed',
'do_sample',
'mirostat_mode',
@ -304,6 +310,8 @@ loaders_samplers = {
'dry_base',
'dry_allowed_length',
'dry_sequence_breakers',
'xtc_threshold',
'xtc_probability',
'seed',
'do_sample',
'mirostat_mode',

29
modules/models.py
View File

@ -70,11 +70,11 @@ def load_model(model_name, loader=None):
shared.model_name = model_name
load_func_map = {
'Transformers': huggingface_loader,
'AutoGPTQ': AutoGPTQ_loader,
'llama.cpp': llamacpp_loader,
'llamacpp_HF': llamacpp_HF_loader,
'ExLlamav2': ExLlamav2_loader,
'ExLlamav2_HF': ExLlamav2_HF_loader,
'AutoGPTQ': AutoGPTQ_loader,
'HQQ': HQQ_loader,
'TensorRT-LLM': TensorRT_LLM_loader,
}
@ -302,12 +302,6 @@ def llamacpp_HF_loader(model_name):
return model
def AutoGPTQ_loader(model_name):
import modules.AutoGPTQ_loader
return modules.AutoGPTQ_loader.load_quantized(model_name)
def ExLlamav2_loader(model_name):
from modules.exllamav2 import Exllamav2Model
@ -321,9 +315,21 @@ def ExLlamav2_HF_loader(model_name):
return Exllamav2HF.from_pretrained(model_name)
def AutoGPTQ_loader(model_name):
try:
import modules.AutoGPTQ_loader
except ModuleNotFoundError:
raise ModuleNotFoundError("Failed to import 'autogptq'. Please install it manually following the instructions in the AutoGPTQ GitHub repository.")
return modules.AutoGPTQ_loader.load_quantized(model_name)
def HQQ_loader(model_name):
from hqq.core.quantize import HQQBackend, HQQLinear
from hqq.models.hf.base import AutoHQQHFModel
try:
from hqq.core.quantize import HQQBackend, HQQLinear
from hqq.models.hf.base import AutoHQQHFModel
except ModuleNotFoundError:
raise ModuleNotFoundError("Failed to import 'hqq'. Please install it manually following the instructions in the HQQ GitHub repository.")
logger.info(f"Loading HQQ model with backend: \"{shared.args.hqq_backend}\"")
@ -334,7 +340,10 @@ def HQQ_loader(model_name):
def TensorRT_LLM_loader(model_name):
from modules.tensorrt_llm import TensorRTLLMModel
try:
from modules.tensorrt_llm import TensorRTLLMModel
except ModuleNotFoundError:
raise ModuleNotFoundError("Failed to import 'tensorrt_llm'. Please install it manually following the instructions in the TensorRT-LLM GitHub repository.")
model = TensorRTLLMModel.from_pretrained(model_name)
return model

4
modules/presets.py
View File

@ -44,7 +44,9 @@ def default_preset():
'dry_base': 1.75,
'dry_allowed_length': 2,
'dry_sequence_breakers': '"\\n", ":", "\\"", "*"',
'sampler_priority': 'temperature\ndynamic_temperature\nquadratic_sampling\ntop_k\ntop_p\ntypical_p\nepsilon_cutoff\neta_cutoff\ntfs\ntop_a\nmin_p\nmirostat'
'xtc_threshold': 0.1,
'xtc_probability': 0,
'sampler_priority': 'repetition_penalty\npresence_penalty\nfrequency_penalty\ndry\ntemperature\ndynamic_temperature\nquadratic_sampling\ntop_k\ntop_p\ntypical_p\nepsilon_cutoff\neta_cutoff\ntfs\ntop_a\nmin_p\nmirostat\nxtc\nencoder_repetition_penalty\nno_repeat_ngram'
}

257
modules/sampler_hijack.py
View File

@ -1,6 +1,7 @@
import json
import math
import pprint
import random
import torch
import transformers
@ -191,6 +192,53 @@ class TopALogitsWarper(LogitsWarper):
return scores
# Exclude Top Choices (XTC)
class XTCLogitsWarper(LogitsWarper):
def __init__(self, threshold: float, probability: float, filter_value: float = -float("Inf")):
self.threshold = threshold
self.probability = probability
self.filter_value = filter_value
self.special_token_ids = [
shared.tokenizer.encode("\n")[-1],
]
if shared.tokenizer.eos_token_id is not None:
self.special_token_ids.append(shared.tokenizer.eos_token_id)
def __call__(self, input_ids: torch.LongTensor, scores: torch.FloatTensor) -> torch.FloatTensor:
# `random` returns values in the half-open range [0, 1), so setting `probability`
# to 0 means the sampler never takes action, while setting it to 1 means the sampler
# always takes action.
#
# Note that while XTC is most intuitively described as "if multiple tokens meet
# the threshold, then with probability...", reversing the two conditions is logically
# equivalent, and improves performance because processing can immediately be stopped
# if the random check fails.
if random.random() >= self.probability:
return scores
sorted_logits, sorted_indices = torch.sort(scores, descending=True)
probs = sorted_logits.softmax(dim=-1)
sorted_indices_to_remove = torch.full_like(probs, False, dtype=torch.bool)
# This operation sets exactly those indices to `True` for which the next index has
# probability above the threshold. Since `probs` is sorted, those are the indices
# of all tokens that meet the threshold, *except* the least probable one.
sorted_indices_to_remove[..., :-1] = probs[..., 1:] >= self.threshold
# Convert sorted_indices_to_remove to the original indices
indices_to_remove = sorted_indices_to_remove.scatter(1, sorted_indices, sorted_indices_to_remove)
# If newline or EOS tokens would be removed, return the original scores
if indices_to_remove[:, self.special_token_ids].any():
return scores
# Otherwise, remove tokens with the mask
scores = scores.masked_fill(indices_to_remove, self.filter_value)
return scores
class DRYLogitsProcessor(LogitsProcessor):
def __init__(self, multiplier: float, base: float, allowed_length: int, sequence_breakers: set[int], _range: int):
self.multiplier = multiplier
@ -323,62 +371,141 @@ class SpyLogitsWarper(LogitsWarper):
class RepetitionPenaltyLogitsProcessorWithRange(LogitsProcessor):
'''
Copied from the transformers library
'''
def __init__(self, penalty: float, presence_penalty: float, frequency_penalty: float, _range: int):
def __init__(self, penalty: float, _range: int):
if not (penalty > 0):
raise ValueError(f"`penalty` has to be strictly positive, but is {penalty}")
self.penalty = penalty
self.presence_penalty = presence_penalty
self.frequency_penalty = frequency_penalty
self._range = _range
def apply_repetition_penalty(self, input_ids_row, scores_row):
unique_ids = torch.unique(input_ids_row)
score = torch.gather(scores_row, 0, unique_ids)
# Apply multiplicative repetition penalty
score = torch.where(score < 0, score * self.penalty, score / self.penalty)
scores_row.scatter_(0, unique_ids, score)
return scores_row
def __call__(self, input_ids: torch.LongTensor, scores: torch.FloatTensor) -> torch.FloatTensor:
input_ids = input_ids[:, -self._range:]
# We loop here because torch.unique() needs to process each row separately in the
# case that batch_size > 1.
for input_ids_row, scores_row in zip(input_ids, scores):
unique_ids, counts = torch.unique(input_ids_row, return_counts=True)
score = torch.gather(scores_row, 0, unique_ids)
# multiplicative repetition penalty
# if score < 0 then repetition penalty has to be multiplied to reduce the previous token probability
score = torch.where(score < 0, score * self.penalty, score / self.penalty)
scores_row.scatter_(0, unique_ids, score)
# presence_penalty and frequency_penalty
raw_presence_penalty = (counts > 0).to(scores.dtype)
raw_frequency_penalty = counts.to(scores.dtype)
additive_penalty = raw_presence_penalty * self.presence_penalty + raw_frequency_penalty * self.frequency_penalty
scores_row.scatter_add_(0, unique_ids, -additive_penalty)
scores_row = self.apply_repetition_penalty(input_ids_row, scores_row)
return scores
def get_logits_warper_patch(self, generation_config, **kwargs):
class PresencePenaltyLogitsProcessor(LogitsProcessor):
def __init__(self, presence_penalty: float, _range: int):
self.presence_penalty = presence_penalty
self._range = _range
def apply_presence_penalty(self, input_ids_row, scores_row):
unique_ids, counts = torch.unique(input_ids_row, return_counts=True)
# Apply presence penalty
raw_presence_penalty = (counts > 0).to(scores_row.dtype)
presence_penalty = raw_presence_penalty * self.presence_penalty
scores_row.scatter_add_(0, unique_ids, -presence_penalty)
return scores_row
def __call__(self, input_ids: torch.LongTensor, scores: torch.FloatTensor) -> torch.FloatTensor:
input_ids = input_ids[:, -self._range:]
for input_ids_row, scores_row in zip(input_ids, scores):
scores_row = self.apply_presence_penalty(input_ids_row, scores_row)
return scores
class FrequencyPenaltyLogitsProcessor(LogitsProcessor):
def __init__(self, frequency_penalty: float, _range: int):
self.frequency_penalty = frequency_penalty
self._range = _range
def apply_frequency_penalty(self, input_ids_row, scores_row):
unique_ids, counts = torch.unique(input_ids_row, return_counts=True)
# Apply frequency penalty
raw_frequency_penalty = counts.to(scores_row.dtype)
frequency_penalty = raw_frequency_penalty * self.frequency_penalty
scores_row.scatter_add_(0, unique_ids, -frequency_penalty)
return scores_row
def __call__(self, input_ids: torch.LongTensor, scores: torch.FloatTensor) -> torch.FloatTensor:
input_ids = input_ids[:, -self._range:]
for input_ids_row, scores_row in zip(input_ids, scores):
scores_row = self.apply_frequency_penalty(input_ids_row, scores_row)
return scores
def get_logits_processor_patch(self, **kwargs):
generation_config = kwargs['generation_config']
# 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, **kwargs)
warpers = self._get_logits_processor_old(**kwargs)
# Replace temperature with our modified class.
# Currently, it behaves identically to the original.
for i in range(len(warpers)):
for i in range(len(warpers) - 1, -1, -1):
# Replace temperature with our modified class.
if warpers[i].__class__.__name__ == 'TemperatureLogitsWarper':
warpers[i] = TemperatureLogitsWarperCustom(
generation_config.temperature,
)
# Stuff we don't need
elif warpers[i].__class__.__name__ in ['SuppressTokensLogitsProcessor', 'RepetitionPenaltyLogitsProcessor']:
del warpers[i]
# Add custom warpers
warpers_to_add = LogitsProcessorList()
min_tokens_to_keep = 2 if generation_config.num_beams > 1 else 1
if generation_config.repetition_penalty is not None and generation_config.repetition_penalty != 1.0:
warpers_to_add.append(
RepetitionPenaltyLogitsProcessorWithRange(
penalty=generation_config.repetition_penalty,
_range=generation_config.repetition_penalty_range
)
)
if generation_config.presence_penalty is not None and generation_config.presence_penalty != 0.0:
warpers_to_add.append(
PresencePenaltyLogitsProcessor(
presence_penalty=generation_config.presence_penalty,
_range=generation_config.repetition_penalty_range
)
)
if generation_config.frequency_penalty is not None and generation_config.frequency_penalty != 0.0:
warpers_to_add.append(
FrequencyPenaltyLogitsProcessor(
frequency_penalty=generation_config.frequency_penalty,
_range=generation_config.repetition_penalty_range
)
)
if generation_config.dry_multiplier is not None and generation_config.dry_multiplier > 0.0:
dry_sequence_breakers = generation_config.dry_sequence_breakers
# Support both JSON array notation and comma-separated strings.
if not dry_sequence_breakers.startswith("["):
dry_sequence_breakers = "[" + dry_sequence_breakers + "]"
sequence_breaker_strings = json.loads(dry_sequence_breakers)
# Prefix with 'a' to get the correct encoding of the token at the end of a text.
sequence_breakers = {shared.tokenizer.encode(f'a{s}')[-1] for s in sequence_breaker_strings}
warpers.append(
DRYLogitsProcessor(
multiplier=generation_config.dry_multiplier,
base=generation_config.dry_base,
allowed_length=generation_config.dry_allowed_length,
sequence_breakers=sequence_breakers,
_range=generation_config.repetition_penalty_range,
)
)
if generation_config.tfs is not None and 0.0 <= generation_config.tfs < 1.0:
warpers_to_add.append(
TailFreeLogitsWarper(
@ -395,6 +522,14 @@ def get_logits_warper_patch(self, generation_config, **kwargs):
)
)
if generation_config.xtc_probability is not None and generation_config.xtc_probability > 0:
warpers_to_add.append(
XTCLogitsWarper(
threshold=generation_config.xtc_threshold,
probability=generation_config.xtc_probability,
)
)
if generation_config.dynamic_temperature:
warpers_to_add.append(
DynamicTemperatureLogitsWarper(
@ -454,17 +589,23 @@ def get_logits_warper_patch(self, generation_config, **kwargs):
'TopALogitsWarper': 'top_a',
'TopKLogitsWarper': 'top_k',
'TopPLogitsWarper': 'top_p',
'TypicalLogitsWarper': 'typical_p'
'TypicalLogitsWarper': 'typical_p',
'XTCLogitsWarper': 'xtc',
'RepetitionPenaltyLogitsProcessorWithRange': 'repetition_penalty',
'PresencePenaltyLogitsProcessor': 'presence_penalty',
'FrequencyPenaltyLogitsProcessor': 'frequency_penalty',
'DRYLogitsProcessor': 'dry',
'EncoderRepetitionPenaltyLogitsProcessor': 'encoder_repetition_penalty',
'NoRepeatNGramLogitsProcessor': 'no_repeat_ngram',
}
def custom_sort_key(obj):
class_name = obj.__class__.__name__
# Return a large value if class name is not mapped or if the mapped nickname is not in priority
# Return -1 if class_name is not mapped
if class_name not in class_name_to_nickname or class_name_to_nickname[class_name] not in sampler_priority:
return float('inf')
return -1
# Return the index of the nickname in the priority list for sorting
return sampler_priority.index(class_name_to_nickname[class_name])
# Sort the list using the custom key function
@ -482,49 +623,6 @@ def get_logits_warper_patch(self, generation_config, **kwargs):
return warpers
def get_logits_processor_patch(self, **kwargs):
generation_config = kwargs['generation_config']
do_rep_pen_hijack = (generation_config.repetition_penalty > 1) or (generation_config.presence_penalty != 0) or (generation_config.frequency_penalty != 0)
if do_rep_pen_hijack:
generation_config.repetition_penalty = 1.1 # Set to value > 1 to ensure RepetitionPenaltyLogitsProcessor is created
result = self._get_logits_processor_old(**kwargs)
if do_rep_pen_hijack:
for i in range(len(result)):
if result[i].__class__.__name__ == 'RepetitionPenaltyLogitsProcessor':
result[i] = RepetitionPenaltyLogitsProcessorWithRange(
generation_config.repetition_penalty,
generation_config.presence_penalty,
generation_config.frequency_penalty,
generation_config.repetition_penalty_range
)
if generation_config.dry_multiplier is not None and generation_config.dry_multiplier > 0.0:
dry_sequence_breakers = generation_config.dry_sequence_breakers
# Support both JSON array notation and comma-separated strings.
if not dry_sequence_breakers.startswith("["):
dry_sequence_breakers = "[" + dry_sequence_breakers + "]"
sequence_breaker_strings = json.loads(dry_sequence_breakers)
# Prefix with 'a' to get the correct encoding of the token at the end of a text.
sequence_breakers = {shared.tokenizer.encode(f'a{s}')[-1] for s in sequence_breaker_strings}
result.append(
DRYLogitsProcessor(
multiplier=generation_config.dry_multiplier,
base=generation_config.dry_base,
allowed_length=generation_config.dry_allowed_length,
sequence_breakers=sequence_breakers,
_range=generation_config.repetition_penalty_range,
)
)
return result
def generation_config_init_patch(self, **kwargs):
self.__init___old(**kwargs)
self.min_p = kwargs.pop("min_p", 0.0)
@ -546,14 +644,13 @@ def generation_config_init_patch(self, **kwargs):
self.dry_base = kwargs.pop("dry_base", 1.75)
self.dry_allowed_length = kwargs.pop("dry_allowed_length", 2)
self.dry_sequence_breakers = kwargs.pop("dry_sequence_breakers", '"\\n", ":", "\\"", "*"')
self.xtc_threshold = kwargs.pop("xtc_threshold", 0.1)
self.xtc_probability = kwargs.pop("xtc_probability", 0)
self.temperature_last = kwargs.pop("temperature_last", False)
self.sampler_priority = kwargs.pop("sampler_priority", ['temperature', 'dynamic_temperature', 'quadratic_sampling', 'top_k', 'top_p', 'typical_p', 'epsilon_cutoff', 'eta_cutoff', 'tfs', 'top_a', 'min_p', 'mirostat'])
self.sampler_priority = kwargs.pop("sampler_priority", ['repetition_penalty', 'presence_penalty', 'frequency_penalty', 'dry', 'temperature', 'dynamic_temperature', 'quadratic_sampling', 'top_k', 'top_p', 'typical_p', 'epsilon_cutoff', 'eta_cutoff', 'tfs', 'top_a', 'min_p', 'mirostat', 'xtc', 'encoder_repetition_penalty', 'no_repeat_ngram'])
def hijack_samplers():
transformers.GenerationMixin._get_logits_warper_old = transformers.GenerationMixin._get_logits_warper
transformers.GenerationMixin._get_logits_warper = get_logits_warper_patch
transformers.GenerationMixin._get_logits_processor_old = transformers.GenerationMixin._get_logits_processor
transformers.GenerationMixin._get_logits_processor = get_logits_processor_patch

1
modules/shared.py
View File

@ -146,6 +146,7 @@ group.add_argument('--no_sdpa', action='store_true', help='Force Torch SDPA to n
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.')
group.add_argument('--enable_tp', action='store_true', help='Enable Tensor Parallelism (TP) in ExLlamaV2.')
# AutoGPTQ
group = parser.add_argument_group('AutoGPTQ')

9
modules/text_generation.py
View File

@ -274,7 +274,12 @@ def get_reply_from_output_ids(output_ids, state=None, starting_from=0):
if (hasattr(shared.tokenizer, 'convert_ids_to_tokens') and len(output_ids) > starting_from) and not reply.startswith(' '):
first_token = shared.tokenizer.convert_ids_to_tokens(int(output_ids[starting_from]))
if isinstance(first_token, (bytes,)):
first_token = first_token.decode('utf8')
# try to decode the bytes to a string
# if it fails, which means it's not a string in this turn, just ignore it
try:
first_token = first_token.decode('utf8')
except UnicodeDecodeError:
first_token = ''
if first_token.startswith('▁'):
reply = ' ' + reply
@ -284,7 +289,7 @@ def get_reply_from_output_ids(output_ids, state=None, starting_from=0):
def generate_reply_HF(question, original_question, seed, state, stopping_strings=None, is_chat=False):
generate_params = {}
for k in ['max_new_tokens', 'temperature', 'temperature_last', 'dynamic_temperature', 'dynatemp_low', 'dynatemp_high', 'dynatemp_exponent', 'smoothing_factor', 'smoothing_curve', 'top_p', 'min_p', 'top_k', 'repetition_penalty', 'presence_penalty', 'frequency_penalty', 'repetition_penalty_range', 'typical_p', 'tfs', 'top_a', 'guidance_scale', 'penalty_alpha', 'mirostat_mode', 'mirostat_tau', 'mirostat_eta', 'do_sample', 'encoder_repetition_penalty', 'no_repeat_ngram_size', 'dry_multiplier', 'dry_base', 'dry_allowed_length', 'dry_sequence_breakers']:
for k in ['max_new_tokens', 'temperature', 'temperature_last', 'dynamic_temperature', 'dynatemp_low', 'dynatemp_high', 'dynatemp_exponent', 'smoothing_factor', 'smoothing_curve', 'top_p', 'min_p', 'top_k', 'repetition_penalty', 'presence_penalty', 'frequency_penalty', 'repetition_penalty_range', 'typical_p', 'tfs', 'top_a', 'guidance_scale', 'penalty_alpha', 'mirostat_mode', 'mirostat_tau', 'mirostat_eta', 'do_sample', 'encoder_repetition_penalty', 'no_repeat_ngram_size', 'dry_multiplier', 'dry_base', 'dry_allowed_length', 'dry_sequence_breakers', 'xtc_threshold', 'xtc_probability']:
if k in state:
generate_params[k] = state[k]

18
modules/training.py
View File

@ -18,14 +18,6 @@ import gradio as gr
import torch
import transformers
from datasets import Dataset, load_dataset
from peft import (
LoraConfig,
get_peft_model,
prepare_model_for_kbit_training,
set_peft_model_state_dict
)
from peft.utils.other import \
TRANSFORMERS_MODELS_TO_LORA_TARGET_MODULES_MAPPING as model_to_lora_modules
from transformers import is_torch_xpu_available
from transformers.models.auto.modeling_auto import (
MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
@ -292,6 +284,16 @@ def calc_trainable_parameters(model):
def do_train(lora_name: str, always_override: bool, q_proj_en: bool, v_proj_en: bool, k_proj_en: bool, o_proj_en: bool, gate_proj_en: bool, down_proj_en: bool, up_proj_en: bool, save_steps: int, micro_batch_size: int, batch_size: int, epochs: int, learning_rate: str, lr_scheduler_type: str, lora_rank: int, lora_alpha: int, lora_dropout: float, cutoff_len: int, dataset: str, eval_dataset: str, format: str, eval_steps: int, raw_text_file: str, overlap_len: int, newline_favor_len: int, higher_rank_limit: bool, warmup_steps: int, optimizer: str, hard_cut_string: str, train_only_after: str, stop_at_loss: float, add_eos_token: bool, min_chars: int, report_to: str):
from peft import (
LoraConfig,
get_peft_model,
prepare_model_for_kbit_training,
set_peft_model_state_dict
)
from peft.utils.other import \
TRANSFORMERS_MODELS_TO_LORA_TARGET_MODULES_MAPPING as \
model_to_lora_modules
global WANT_INTERRUPT
WANT_INTERRUPT = False

3
modules/ui.py
View File

@ -90,6 +90,7 @@ def list_model_elements():
'cache_8bit',
'cache_4bit',
'autosplit',
'enable_tp',
'threads',
'threads_batch',
'n_batch',
@ -158,6 +159,8 @@ def list_interface_input_elements():
'dry_base',
'dry_allowed_length',
'dry_sequence_breakers',
'xtc_threshold',
'xtc_probability',
'do_sample',
'penalty_alpha',
'mirostat_mode',

2
modules/ui_file_saving.py
View File

@ -74,7 +74,7 @@ def handle_save_preset_confirm_click(filename, contents):
try:
utils.save_file(f"presets/{filename}.yaml", contents)
available_presets = utils.get_available_presets()
output = gr.update(choices=available_presets, value=filename),
output = gr.update(choices=available_presets, value=filename)
except Exception:
output = gr.update()
traceback.print_exc()

1
modules/ui_model_menu.py
View File

@ -136,6 +136,7 @@ def create_ui():
shared.gradio['disk'] = gr.Checkbox(label="disk", value=shared.args.disk)
shared.gradio['bf16'] = gr.Checkbox(label="bf16", value=shared.args.bf16)
shared.gradio['autosplit'] = gr.Checkbox(label="autosplit", value=shared.args.autosplit, info='Automatically split the model tensors across the available GPUs.')
shared.gradio['enable_tp'] = gr.Checkbox(label="enable_tp", value=shared.args.enable_tp, info='Enable Tensor Parallelism (TP).')
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)

4
modules/ui_parameters.py
View File

@ -45,6 +45,10 @@ def create_ui(default_preset):
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_sequence_breakers'] = gr.Textbox(value=generate_params['dry_sequence_breakers'], label='dry_sequence_breakers', info='Tokens across which sequence matching is not continued. Specified as a comma-separated list of quoted strings.')
with gr.Blocks():
shared.gradio['xtc_threshold'] = gr.Slider(0, 0.5, value=generate_params['xtc_threshold'], step=0.01, label='xtc_threshold', info='If 2 or more tokens have probability above this threshold, consider removing all but the last one.')
shared.gradio['xtc_probability'] = gr.Slider(0, 1, value=generate_params['xtc_probability'], step=0.01, label='xtc_probability', info='Probability that the removal will actually happen. 0 disables the sampler. 1 makes it always happen.')
gr.Markdown("[Learn more](https://github.com/oobabooga/text-generation-webui/wiki/03-%E2%80%90-Parameters-Tab)")
with gr.Column():

17
one_click.py
View File

@ -16,9 +16,9 @@ import sys
# Define the required PyTorch version
TORCH_VERSION = "2.2.2"
TORCHVISION_VERSION = "0.17.2"
TORCHAUDIO_VERSION = "2.2.2"
TORCH_VERSION = "2.4.1"
TORCHVISION_VERSION = "0.19.1"
TORCHAUDIO_VERSION = "2.4.1"
# Environment
script_dir = os.getcwd()
@ -117,7 +117,7 @@ def update_pytorch():
elif is_cuda:
install_pytorch += "--index-url https://download.pytorch.org/whl/cu121"
elif is_rocm:
install_pytorch += "--index-url https://download.pytorch.org/whl/rocm5.6"
install_pytorch += "--index-url https://download.pytorch.org/whl/rocm6.1"
elif is_cpu:
install_pytorch += "--index-url https://download.pytorch.org/whl/cpu"
elif is_intel:
@ -189,8 +189,11 @@ def run_cmd(cmd, assert_success=False, environment=False, capture_output=False,
conda_sh_path = os.path.join(script_dir, "installer_files", "conda", "etc", "profile.d", "conda.sh")
cmd = f'. "{conda_sh_path}" && conda activate "{conda_env_path}" && {cmd}'
# Set executable to None for Windows, /bin/bash for everything else
executable = None if is_windows() else '/bin/bash'
# Run shell commands
result = subprocess.run(cmd, shell=True, capture_output=capture_output, env=env)
result = subprocess.run(cmd, shell=True, capture_output=capture_output, env=env, executable=executable)
# Assert the command ran successfully
if assert_success and result.returncode != 0:
@ -239,7 +242,7 @@ def install_webui():
"What is your GPU?",
{
'A': 'NVIDIA',
'B': 'AMD (Linux/MacOS only. Requires ROCm SDK 5.6 on Linux)',
'B': 'AMD (Linux/MacOS only. Requires ROCm SDK 6.1 on Linux)',
'C': 'Apple M Series',
'D': 'Intel Arc (IPEX)',
'N': 'None (I want to run models in CPU mode)'
@ -294,7 +297,7 @@ def install_webui():
else:
install_pytorch += "--index-url https://download.pytorch.org/whl/cu121"
elif selected_gpu == "AMD":
install_pytorch += "--index-url https://download.pytorch.org/whl/rocm5.6"
install_pytorch += "--index-url https://download.pytorch.org/whl/rocm6.1"
elif selected_gpu in ["APPLE", "NONE"]:
install_pytorch += "--index-url https://download.pytorch.org/whl/cpu"
elif selected_gpu == "INTEL":

59
requirements.txt
View File

@ -1,12 +1,10 @@
accelerate==0.33.*
aqlm[gpu,cpu]==1.1.6; platform_system == "Linux"
auto-gptq==0.7.1
bitsandbytes==0.43.*
bitsandbytes==0.44.*
colorama
datasets
einops
fastapi==0.112.4
gradio==4.26.*
hqq==0.1.7.post3
jinja2==3.1.4
lm_eval==0.3.0
markdown
@ -17,6 +15,7 @@ pandas
peft==0.12.*
Pillow>=9.5.0
psutil
pydantic==2.8.2
pyyaml
requests
rich
@ -24,7 +23,7 @@ safetensors==0.4.*
scipy
sentencepiece
tensorboard
transformers==4.44.*
transformers==4.45.*
tqdm
wandb
@ -35,38 +34,30 @@ 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-0.2.89+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-0.2.89+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-0.2.89+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-0.2.89+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-0.3.1+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-0.3.1+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-0.3.1+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-0.3.1+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-0.2.89+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-0.2.89+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-0.2.89+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-0.2.89+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-0.3.1+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-0.3.1+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-0.3.1+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-0.3.1+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-0.2.89+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-0.2.89+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-0.2.89+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-0.2.89+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-0.3.1+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-0.3.1+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-0.3.1+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-0.3.1+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/v0.1.8/exllamav2-0.1.8+cu121.torch2.2.2-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
https://github.com/oobabooga/exllamav2/releases/download/v0.1.8/exllamav2-0.1.8+cu121.torch2.2.2-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
https://github.com/oobabooga/exllamav2/releases/download/v0.1.8/exllamav2-0.1.8+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/v0.1.8/exllamav2-0.1.8+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/v0.1.8/exllamav2-0.1.8-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"
https://github.com/oobabooga/AutoAWQ/releases/download/0.2.6/autoawq-0.2.6-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
https://github.com/oobabooga/AutoAWQ/releases/download/0.2.6/autoawq-0.2.6-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
https://github.com/oobabooga/AutoAWQ/releases/download/0.2.6/autoawq-0.2.6-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
https://github.com/oobabooga/AutoAWQ/releases/download/0.2.6/autoawq-0.2.6-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
https://github.com/oobabooga/AutoAWQ_kernels/releases/download/0.0.7/autoawq_kernels-0.0.7-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
https://github.com/oobabooga/AutoAWQ_kernels/releases/download/0.0.7/autoawq_kernels-0.0.7-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
https://github.com/oobabooga/AutoAWQ_kernels/releases/download/0.0.7/autoawq_kernels-0.0.7-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
https://github.com/oobabooga/AutoAWQ_kernels/releases/download/0.0.7/autoawq_kernels-0.0.7-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/v0.2.3/exllamav2-0.2.3+cu121.torch2.4.1-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
https://github.com/oobabooga/exllamav2/releases/download/v0.2.3/exllamav2-0.2.3+cu121.torch2.4.1-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
https://github.com/oobabooga/exllamav2/releases/download/v0.2.3/exllamav2-0.2.3+cu121.torch2.4.1-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/v0.2.3/exllamav2-0.2.3+cu121.torch2.4.1-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/v0.2.3/exllamav2-0.2.3-py3-none-any.whl; platform_system == "Linux" and platform_machine != "x86_64"
https://github.com/oobabooga/flash-attention/releases/download/v2.6.3/flash_attn-2.6.3+cu122torch2.4.1cxx11abiFALSE-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
https://github.com/oobabooga/flash-attention/releases/download/v2.6.3/flash_attn-2.6.3+cu122torch2.4.1cxx11abiFALSE-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
https://github.com/Dao-AILab/flash-attention/releases/download/v2.6.3/flash_attn-2.6.3+cu123torch2.4cxx11abiFALSE-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/v2.6.3/flash_attn-2.6.3+cu123torch2.4cxx11abiFALSE-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"

27
requirements_amd.txt
View File

@ -2,8 +2,8 @@ accelerate==0.33.*
colorama
datasets
einops
fastapi==0.112.4
gradio==4.26.*
hqq==0.1.7.post3
jinja2==3.1.4
lm_eval==0.3.0
markdown
@ -14,6 +14,7 @@ pandas
peft==0.12.*
Pillow>=9.5.0
psutil
pydantic==2.8.2
pyyaml
requests
rich
@ -21,7 +22,7 @@ safetensors==0.4.*
scipy
sentencepiece
tensorboard
transformers==4.44.*
transformers==4.45.*
tqdm
wandb
@ -32,18 +33,14 @@ 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-0.2.89+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-0.2.89+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-0.2.89+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-0.2.89+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-0.3.1+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-0.3.1+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-0.3.1+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-0.3.1+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-0.2.89+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-0.2.89+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/v0.1.8/exllamav2-0.1.8+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/v0.1.8/exllamav2-0.1.8+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/v0.1.8/exllamav2-0.1.8-py3-none-any.whl; platform_system != "Darwin" and platform_machine != "x86_64"
https://github.com/oobabooga/AutoAWQ/releases/download/0.2.6/autoawq-0.2.6-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
https://github.com/oobabooga/AutoAWQ/releases/download/0.2.6/autoawq-0.2.6-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
https://github.com/oobabooga/AutoAWQ_kernels/releases/download/0.0.7/autoawq_kernels-0.0.7+rocm561-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
https://github.com/oobabooga/AutoAWQ_kernels/releases/download/0.0.7/autoawq_kernels-0.0.7+rocm561-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/rocm/llama_cpp_python_cuda-0.3.1+rocm6.1.2-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-0.3.1+rocm6.1.2-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/v0.2.3/exllamav2-0.2.3+rocm6.1.torch2.4.1-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/v0.2.3/exllamav2-0.2.3+rocm6.1.torch2.4.1-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/v0.2.3/exllamav2-0.2.3-py3-none-any.whl; platform_system != "Darwin" and platform_machine != "x86_64"

23
requirements_amd_noavx2.txt
View File

@ -2,8 +2,8 @@ accelerate==0.33.*
colorama
datasets
einops
fastapi==0.112.4
gradio==4.26.*
hqq==0.1.7.post3
jinja2==3.1.4
lm_eval==0.3.0
markdown
@ -14,6 +14,7 @@ pandas
peft==0.12.*
Pillow>=9.5.0
psutil
pydantic==2.8.2
pyyaml
requests
rich
@ -21,7 +22,7 @@ safetensors==0.4.*
scipy
sentencepiece
tensorboard
transformers==4.44.*
transformers==4.45.*
tqdm
wandb
@ -32,16 +33,12 @@ 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-0.2.89+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-0.2.89+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-0.2.89+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-0.2.89+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-0.3.1+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-0.3.1+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-0.3.1+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-0.3.1+cpuavx-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
# AMD wheels
https://github.com/oobabooga/exllamav2/releases/download/v0.1.8/exllamav2-0.1.8+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/v0.1.8/exllamav2-0.1.8+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/v0.1.8/exllamav2-0.1.8-py3-none-any.whl; platform_system != "Darwin" and platform_machine != "x86_64"
https://github.com/oobabooga/AutoAWQ/releases/download/0.2.6/autoawq-0.2.6-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
https://github.com/oobabooga/AutoAWQ/releases/download/0.2.6/autoawq-0.2.6-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
https://github.com/oobabooga/AutoAWQ_kernels/releases/download/0.0.7/autoawq_kernels-0.0.7+rocm561-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
https://github.com/oobabooga/AutoAWQ_kernels/releases/download/0.0.7/autoawq_kernels-0.0.7+rocm561-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/v0.2.3/exllamav2-0.2.3+rocm6.1.torch2.4.1-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/v0.2.3/exllamav2-0.2.3+rocm6.1.torch2.4.1-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/v0.2.3/exllamav2-0.2.3-py3-none-any.whl; platform_system != "Darwin" and platform_machine != "x86_64"

15
requirements_apple_intel.txt
View File

@ -2,8 +2,8 @@ accelerate==0.33.*
colorama
datasets
einops
fastapi==0.112.4
gradio==4.26.*
hqq==0.1.7.post3
jinja2==3.1.4
lm_eval==0.3.0
markdown
@ -14,6 +14,7 @@ pandas
peft==0.12.*
Pillow>=9.5.0
psutil
pydantic==2.8.2
pyyaml
requests
rich
@ -21,7 +22,7 @@ safetensors==0.4.*
scipy
sentencepiece
tensorboard
transformers==4.44.*
transformers==4.45.*
tqdm
wandb
@ -32,8 +33,8 @@ sse-starlette==1.6.5
tiktoken
# Mac wheels
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/metal/llama_cpp_python-0.2.89-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-0.2.89-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-0.2.89-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-0.2.89-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/v0.1.8/exllamav2-0.1.8-py3-none-any.whl
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/metal/llama_cpp_python-0.3.1-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-0.3.1-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-0.3.1-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-0.3.1-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/v0.2.3/exllamav2-0.2.3-py3-none-any.whl

19
requirements_apple_silicon.txt
View File

@ -2,8 +2,8 @@ accelerate==0.33.*
colorama
datasets
einops
fastapi==0.112.4
gradio==4.26.*
hqq==0.1.7.post3
jinja2==3.1.4
lm_eval==0.3.0
markdown
@ -14,6 +14,7 @@ pandas
peft==0.12.*
Pillow>=9.5.0
psutil
pydantic==2.8.2
pyyaml
requests
rich
@ -21,7 +22,7 @@ safetensors==0.4.*
scipy
sentencepiece
tensorboard
transformers==4.44.*
transformers==4.45.*
tqdm
wandb
@ -32,10 +33,10 @@ sse-starlette==1.6.5
tiktoken
# Mac wheels
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/metal/llama_cpp_python-0.2.89-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-0.2.89-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-0.2.89-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-0.2.89-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-0.2.89-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-0.2.89-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/v0.1.8/exllamav2-0.1.8-py3-none-any.whl
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/metal/llama_cpp_python-0.3.1-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-0.3.1-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-0.3.1-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-0.3.1-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-0.3.1-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-0.3.1-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/v0.2.3/exllamav2-0.2.3-py3-none-any.whl

13
requirements_cpu_only.txt
View File

@ -2,8 +2,8 @@ accelerate==0.33.*
colorama
datasets
einops
fastapi==0.112.4
gradio==4.26.*
hqq==0.1.7.post3
jinja2==3.1.4
lm_eval==0.3.0
markdown
@ -14,6 +14,7 @@ pandas
peft==0.12.*
Pillow>=9.5.0
psutil
pydantic==2.8.2
pyyaml
requests
rich
@ -21,7 +22,7 @@ safetensors==0.4.*
scipy
sentencepiece
tensorboard
transformers==4.44.*
transformers==4.45.*
tqdm
wandb
@ -32,7 +33,7 @@ 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-0.2.89+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-0.2.89+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-0.2.89+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-0.2.89+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-0.3.1+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-0.3.1+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-0.3.1+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-0.3.1+cpuavx2-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"

13
requirements_cpu_only_noavx2.txt
View File

@ -2,8 +2,8 @@ accelerate==0.33.*
colorama
datasets
einops
fastapi==0.112.4
gradio==4.26.*
hqq==0.1.7.post3
jinja2==3.1.4
lm_eval==0.3.0
markdown
@ -14,6 +14,7 @@ pandas
peft==0.12.*
Pillow>=9.5.0
psutil
pydantic==2.8.2
pyyaml
requests
rich
@ -21,7 +22,7 @@ safetensors==0.4.*
scipy
sentencepiece
tensorboard
transformers==4.44.*
transformers==4.45.*
tqdm
wandb
@ -32,7 +33,7 @@ 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-0.2.89+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-0.2.89+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-0.2.89+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-0.2.89+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-0.3.1+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-0.3.1+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-0.3.1+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-0.3.1+cpuavx-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"

59
requirements_noavx2.txt
View File

@ -1,12 +1,10 @@
accelerate==0.33.*
aqlm[gpu,cpu]==1.1.6; platform_system == "Linux"
auto-gptq==0.7.1
bitsandbytes==0.43.*
bitsandbytes==0.44.*
colorama
datasets
einops
fastapi==0.112.4
gradio==4.26.*
hqq==0.1.7.post3
jinja2==3.1.4
lm_eval==0.3.0
markdown
@ -17,6 +15,7 @@ pandas
peft==0.12.*
Pillow>=9.5.0
psutil
pydantic==2.8.2
pyyaml
requests
rich
@ -24,7 +23,7 @@ safetensors==0.4.*
scipy
sentencepiece
tensorboard
transformers==4.44.*
transformers==4.45.*
tqdm
wandb
@ -35,38 +34,30 @@ 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-0.2.89+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-0.2.89+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-0.2.89+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-0.2.89+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-0.3.1+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-0.3.1+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-0.3.1+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-0.3.1+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-0.2.89+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-0.2.89+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-0.2.89+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-0.2.89+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-0.3.1+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-0.3.1+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-0.3.1+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-0.3.1+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-0.2.89+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-0.2.89+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-0.2.89+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-0.2.89+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-0.3.1+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-0.3.1+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-0.3.1+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-0.3.1+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/v0.1.8/exllamav2-0.1.8+cu121.torch2.2.2-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
https://github.com/oobabooga/exllamav2/releases/download/v0.1.8/exllamav2-0.1.8+cu121.torch2.2.2-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
https://github.com/oobabooga/exllamav2/releases/download/v0.1.8/exllamav2-0.1.8+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/v0.1.8/exllamav2-0.1.8+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/v0.1.8/exllamav2-0.1.8-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"
https://github.com/oobabooga/AutoAWQ/releases/download/0.2.6/autoawq-0.2.6-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
https://github.com/oobabooga/AutoAWQ/releases/download/0.2.6/autoawq-0.2.6-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
https://github.com/oobabooga/AutoAWQ/releases/download/0.2.6/autoawq-0.2.6-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
https://github.com/oobabooga/AutoAWQ/releases/download/0.2.6/autoawq-0.2.6-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
https://github.com/oobabooga/AutoAWQ_kernels/releases/download/0.0.7/autoawq_kernels-0.0.7-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
https://github.com/oobabooga/AutoAWQ_kernels/releases/download/0.0.7/autoawq_kernels-0.0.7-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
https://github.com/oobabooga/AutoAWQ_kernels/releases/download/0.0.7/autoawq_kernels-0.0.7-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
https://github.com/oobabooga/AutoAWQ_kernels/releases/download/0.0.7/autoawq_kernels-0.0.7-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/v0.2.3/exllamav2-0.2.3+cu121.torch2.4.1-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
https://github.com/oobabooga/exllamav2/releases/download/v0.2.3/exllamav2-0.2.3+cu121.torch2.4.1-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
https://github.com/oobabooga/exllamav2/releases/download/v0.2.3/exllamav2-0.2.3+cu121.torch2.4.1-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/v0.2.3/exllamav2-0.2.3+cu121.torch2.4.1-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/v0.2.3/exllamav2-0.2.3-py3-none-any.whl; platform_system == "Linux" and platform_machine != "x86_64"
https://github.com/oobabooga/flash-attention/releases/download/v2.6.3/flash_attn-2.6.3+cu122torch2.4.1cxx11abiFALSE-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
https://github.com/oobabooga/flash-attention/releases/download/v2.6.3/flash_attn-2.6.3+cu122torch2.4.1cxx11abiFALSE-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
https://github.com/Dao-AILab/flash-attention/releases/download/v2.6.3/flash_attn-2.6.3+cu123torch2.4cxx11abiFALSE-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/v2.6.3/flash_attn-2.6.3+cu123torch2.4cxx11abiFALSE-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"

5
requirements_nowheels.txt
View File

@ -2,8 +2,8 @@ accelerate==0.33.*
colorama
datasets
einops
fastapi==0.112.4
gradio==4.26.*
hqq==0.1.7.post3
jinja2==3.1.4
lm_eval==0.3.0
markdown
@ -14,6 +14,7 @@ pandas
peft==0.12.*
Pillow>=9.5.0
psutil
pydantic==2.8.2
pyyaml
requests
rich
@ -21,7 +22,7 @@ safetensors==0.4.*
scipy
sentencepiece
tensorboard
transformers==4.44.*
transformers==4.45.*
tqdm
wandb