Add back my llama-cpp-python wheels, bump to 0.2.65 (#5964)

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oobabooga 2024-04-30 09:11:31 -03:00 committed by GitHub
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18 changed files with 330 additions and 56 deletions

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@ -107,13 +107,16 @@ pip install -r <requirements file according to table below>
Requirements file to use: Requirements file to use:
| GPU | requirements file to use | | GPU | CPU | requirements file to use |
|--------|---------| |--------|---------|---------|
| NVIDIA | `requirements.txt` | | NVIDIA | has AVX2 | `requirements.txt` |
| AMD | `requirements_amd.txt` | | NVIDIA | no AVX2 | `requirements_noavx2.txt` |
| CPU only | `requirements_cpu_only.txt` | | AMD | has AVX2 | `requirements_amd.txt` |
| Apple Intel | `requirements_apple_intel.txt` | | AMD | no AVX2 | `requirements_amd_noavx2.txt` |
| Apple Silicon | `requirements_apple_silicon.txt` | | CPU only | has AVX2 | `requirements_cpu_only.txt` |
| CPU only | no AVX2 | `requirements_cpu_only_noavx2.txt` |
| Apple | Intel | `requirements_apple_intel.txt` |
| Apple | Apple Silicon | `requirements_apple_silicon.txt` |
### Start the web UI ### Start the web UI
@ -129,7 +132,7 @@ Then browse to
##### AMD GPU on Windows ##### AMD GPU on Windows
1) Use `requirements_cpu_only.txt` in the command above. 1) Use `requirements_cpu_only.txt` or `requirements_cpu_only_noavx2.txt` in the command above.
2) Manually install llama-cpp-python using the appropriate command for your hardware: [Installation from PyPI](https://github.com/abetlen/llama-cpp-python#installation-with-hardware-acceleration). 2) Manually install llama-cpp-python using the appropriate command for your hardware: [Installation from PyPI](https://github.com/abetlen/llama-cpp-python#installation-with-hardware-acceleration).
* Use the `LLAMA_HIPBLAS=on` toggle. * Use the `LLAMA_HIPBLAS=on` toggle.
@ -252,6 +255,7 @@ List of command-line flags
| Flag | Description | | Flag | Description |
|-------------|-------------| |-------------|-------------|
| `--tensorcores` | Use llama-cpp-python compiled with tensor cores support. This increases performance on RTX cards. NVIDIA only. |
| `--n_ctx N_CTX` | Size of the prompt context. | | `--n_ctx N_CTX` | Size of the prompt context. |
| `--threads` | Number of threads to use. | | `--threads` | Number of threads to use. |
| `--threads-batch THREADS_BATCH` | Number of threads to use for batches/prompt processing. | | `--threads-batch THREADS_BATCH` | Number of threads to use for batches/prompt processing. |

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@ -21,7 +21,7 @@ Options:
* **alpha_value**: Used to extend the context length of a model with a minor loss in quality. I have measured 1.75 to be optimal for 1.5x context, and 2.5 for 2x context. That is, with alpha = 2.5 you can make a model with 4096 context length go to 8192 context length. * **alpha_value**: Used to extend the context length of a model with a minor loss in quality. I have measured 1.75 to be optimal for 1.5x context, and 2.5 for 2x context. That is, with alpha = 2.5 you can make a model with 4096 context length go to 8192 context length.
* **rope_freq_base**: Originally another way to write "alpha_value", it ended up becoming a necessary parameter for some models like CodeLlama, which was fine-tuned with this set to 1000000 and hence needs to be loaded with it set to 1000000 as well. * **rope_freq_base**: Originally another way to write "alpha_value", it ended up becoming a necessary parameter for some models like CodeLlama, which was fine-tuned with this set to 1000000 and hence needs to be loaded with it set to 1000000 as well.
* **compress_pos_emb**: The first and original context-length extension method, discovered by [kaiokendev](https://kaiokendev.github.io/til). When set to 2, the context length is doubled, 3 and it's tripled, etc. It should only be used for models that have been fine-tuned with this parameter set to different than 1. For models that have not been tuned to have greater context length, alpha_value will lead to a smaller accuracy loss. * **compress_pos_emb**: The first and original context-length extension method, discovered by [kaiokendev](https://kaiokendev.github.io/til). When set to 2, the context length is doubled, 3 and it's tripled, etc. It should only be used for models that have been fine-tuned with this parameter set to different than 1. For models that have not been tuned to have greater context length, alpha_value will lead to a smaller accuracy loss.
* **cpu**: Loads the model in CPU mode using Pytorch. The model will be loaded in 32-bit precision, so a lot of RAM will be used. CPU inference with transformers is older than llama.cpp and it works, but it's a lot slower. * **cpu**: Loads the model in CPU mode using Pytorch. The model will be loaded in 32-bit precision, so a lot of RAM will be used. CPU inference with transformers is older than llama.cpp and it works, but it's a lot slower. Note: this parameter has a different interpretation in the llama.cpp loader (see below).
* **load-in-8bit**: Load the model in 8-bit precision using bitsandbytes. The 8-bit kernel in that library has been optimized for training and not inference, so load-in-8bit is slower than load-in-4bit (but more accurate). * **load-in-8bit**: Load the model in 8-bit precision using bitsandbytes. The 8-bit kernel in that library has been optimized for training and not inference, so load-in-8bit is slower than load-in-4bit (but more accurate).
* **bf16**: Use bfloat16 precision instead of float16 (the default). Only applies when quantization is not used. * **bf16**: Use bfloat16 precision instead of float16 (the default). Only applies when quantization is not used.
* **auto-devices**: When checked, the backend will try to guess a reasonable value for "gpu-memory" to allow you to load a model with CPU offloading. I recommend just setting "gpu-memory" manually instead. This parameter is also needed for loading GPTQ models, in which case it needs to be checked before loading the model. * **auto-devices**: When checked, the backend will try to guess a reasonable value for "gpu-memory" to allow you to load a model with CPU offloading. I recommend just setting "gpu-memory" manually instead. This parameter is also needed for loading GPTQ models, in which case it needs to be checked before loading the model.
@ -84,7 +84,9 @@ Example: https://huggingface.co/TheBloke/Llama-2-7b-Chat-GGUF
* **n_batch**: Batch size for prompt processing. Higher values are supposed to make generation faster, but I have never obtained any benefit from changing this value. * **n_batch**: Batch size for prompt processing. Higher values are supposed to make generation faster, but I have never obtained any benefit from changing this value.
* **threads**: Number of threads. Recommended value: your number of physical cores. * **threads**: Number of threads. Recommended value: your number of physical cores.
* **threads_batch**: Number of threads for batch processing. Recommended value: your total number of cores (physical + virtual). * **threads_batch**: Number of threads for batch processing. Recommended value: your total number of cores (physical + virtual).
* **tensorcores**: Use llama.cpp compiled with "tensor cores" support, which improves performance on NVIDIA RTX cards in most cases.
* **streamingllm**: Experimental feature to avoid re-evaluating the entire prompt when part of it is removed, for instance, when you hit the context length for the model in chat mode and an old message is removed. * **streamingllm**: Experimental feature to avoid re-evaluating the entire prompt when part of it is removed, for instance, when you hit the context length for the model in chat mode and an old message is removed.
* **cpu**: Force a version of llama.cpp compiled without GPU acceleration to be used. Can usually be ignored. Only set this if you want to use CPU only and llama.cpp doesn't work otherwise.
* **no_mul_mat_q**: Disable the mul_mat_q kernel. This kernel usually improves generation speed significantly. This option to disable it is included in case it doesn't work on some system. * **no_mul_mat_q**: Disable the mul_mat_q kernel. This kernel usually improves generation speed significantly. This option to disable it is included in case it doesn't work on some system.
* **no-mmap**: Loads the model into memory at once, possibly preventing I/O operations later on at the cost of a longer load time. * **no-mmap**: Loads the model into memory at once, possibly preventing I/O operations later on at the cost of a longer load time.
* **mlock**: Force the system to keep the model in RAM rather than swapping or compressing (no idea what this means, never used it). * **mlock**: Force the system to keep the model in RAM rather than swapping or compressing (no idea what this means, never used it).

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@ -1,11 +1,25 @@
from typing import Sequence from typing import Sequence
import llama_cpp
from tqdm import tqdm from tqdm import tqdm
from modules import shared from modules import shared
from modules.cache_utils import process_llamacpp_cache from modules.cache_utils import process_llamacpp_cache
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 eval_with_progress(self, tokens: Sequence[int]): def eval_with_progress(self, tokens: Sequence[int]):
""" """
@ -67,7 +81,7 @@ def monkey_patch_generate(lib):
lib.Llama.generate = my_generate lib.Llama.generate = my_generate
for lib in [llama_cpp]: for lib in [llama_cpp, llama_cpp_cuda, llama_cpp_cuda_tensorcores]:
if lib is not None: if lib is not None:
lib.Llama.eval = eval_with_progress lib.Llama.eval = eval_with_progress
monkey_patch_generate(lib) monkey_patch_generate(lib)

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@ -2,7 +2,6 @@ import os
from pathlib import Path from pathlib import Path
from typing import Any, Dict, Optional, Union from typing import Any, Dict, Optional, Union
import llama_cpp
import torch import torch
from torch.nn import CrossEntropyLoss from torch.nn import CrossEntropyLoss
from transformers import GenerationConfig, PretrainedConfig, PreTrainedModel from transformers import GenerationConfig, PretrainedConfig, PreTrainedModel
@ -11,6 +10,32 @@ from transformers.modeling_outputs import CausalLMOutputWithPast
from modules import RoPE, llama_cpp_python_hijack, shared from modules import RoPE, llama_cpp_python_hijack, shared
from modules.logging_colors import logger 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): class LlamacppHF(PreTrainedModel):
def __init__(self, model, path): def __init__(self, model, path):
@ -32,7 +57,7 @@ class LlamacppHF(PreTrainedModel):
'n_tokens': self.model.n_tokens, 'n_tokens': self.model.n_tokens,
'input_ids': self.model.input_ids.copy(), 'input_ids': self.model.input_ids.copy(),
'scores': self.model.scores.copy(), 'scores': self.model.scores.copy(),
'ctx': llama_cpp.llama_new_context_with_model(model.model, model.context_params) 'ctx': llama_cpp_lib().llama_new_context_with_model(model.model, model.context_params)
} }
def _validate_model_class(self): def _validate_model_class(self):
@ -195,7 +220,7 @@ class LlamacppHF(PreTrainedModel):
'split_mode': 1 if not shared.args.row_split else 2 'split_mode': 1 if not shared.args.row_split else 2
} }
Llama = llama_cpp.Llama Llama = llama_cpp_lib().Llama
model = Llama(**params) model = Llama(**params)
return LlamacppHF(model, model_file) return LlamacppHF(model, model_file)

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@ -1,7 +1,6 @@
import re import re
from functools import partial from functools import partial
import llama_cpp
import numpy as np import numpy as np
import torch import torch
@ -10,6 +9,32 @@ from modules.callbacks import Iteratorize
from modules.logging_colors import logger from modules.logging_colors import logger
from modules.text_generation import get_max_prompt_length 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): def ban_eos_logits_processor(eos_token, input_ids, logits):
logits[eos_token] = -float('inf') logits[eos_token] = -float('inf')
@ -35,8 +60,8 @@ class LlamaCppModel:
@classmethod @classmethod
def from_pretrained(self, path): def from_pretrained(self, path):
Llama = llama_cpp.Llama Llama = llama_cpp_lib().Llama
LlamaCache = llama_cpp.LlamaCache LlamaCache = llama_cpp_lib().LlamaCache
result = self() result = self()
cache_capacity = 0 cache_capacity = 0
@ -101,12 +126,12 @@ class LlamaCppModel:
if string != self.grammar_string: if string != self.grammar_string:
self.grammar_string = string self.grammar_string = string
if string.strip() != '': if string.strip() != '':
self.grammar = llama_cpp.LlamaGrammar.from_string(string) self.grammar = llama_cpp_lib().LlamaGrammar.from_string(string)
else: else:
self.grammar = None self.grammar = None
def generate(self, prompt, state, callback=None): def generate(self, prompt, state, callback=None):
LogitsProcessorList = llama_cpp.LogitsProcessorList LogitsProcessorList = llama_cpp_lib().LogitsProcessorList
prompt = prompt if type(prompt) is str else prompt.decode() prompt = prompt if type(prompt) is str else prompt.decode()
# Handle truncation # Handle truncation

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@ -41,9 +41,11 @@ loaders_and_params = OrderedDict({
'alpha_value', 'alpha_value',
'rope_freq_base', 'rope_freq_base',
'compress_pos_emb', 'compress_pos_emb',
'cpu',
'numa', 'numa',
'no_offload_kqv', 'no_offload_kqv',
'row_split', 'row_split',
'tensorcores',
'streaming_llm', 'streaming_llm',
'attention_sink_size', 'attention_sink_size',
], ],
@ -60,6 +62,7 @@ loaders_and_params = OrderedDict({
'alpha_value', 'alpha_value',
'rope_freq_base', 'rope_freq_base',
'compress_pos_emb', 'compress_pos_emb',
'cpu',
'numa', 'numa',
'cfg_cache', 'cfg_cache',
'trust_remote_code', 'trust_remote_code',
@ -67,6 +70,7 @@ loaders_and_params = OrderedDict({
'logits_all', 'logits_all',
'no_offload_kqv', 'no_offload_kqv',
'row_split', 'row_split',
'tensorcores',
'streaming_llm', 'streaming_llm',
'attention_sink_size', 'attention_sink_size',
'llamacpp_HF_info', 'llamacpp_HF_info',

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@ -114,6 +114,7 @@ group.add_argument('--quant_type', type=str, default='nf4', help='quant_type for
# llama.cpp # llama.cpp
group = parser.add_argument_group('llama.cpp') group = parser.add_argument_group('llama.cpp')
group.add_argument('--tensorcores', action='store_true', help='Use llama-cpp-python compiled with tensor cores support. This increases performance on RTX cards. NVIDIA only.')
group.add_argument('--n_ctx', type=int, default=2048, help='Size of the prompt context.') group.add_argument('--n_ctx', type=int, default=2048, help='Size of the prompt context.')
group.add_argument('--threads', type=int, default=0, help='Number of threads to use.') group.add_argument('--threads', type=int, default=0, help='Number of threads to use.')
group.add_argument('--threads-batch', type=int, default=0, help='Number of threads to use for batches/prompt processing.') group.add_argument('--threads-batch', type=int, default=0, help='Number of threads to use for batches/prompt processing.')
@ -204,8 +205,7 @@ group = parser.add_argument_group('Multimodal')
group.add_argument('--multimodal-pipeline', type=str, default=None, help='The multimodal pipeline to use. Examples: llava-7b, llava-13b.') group.add_argument('--multimodal-pipeline', type=str, default=None, help='The multimodal pipeline to use. Examples: llava-7b, llava-13b.')
# Deprecated parameters # Deprecated parameters
group = parser.add_argument_group('Deprecated') # group = parser.add_argument_group('Deprecated')
group.add_argument('--tensorcores', action='store_true', help='DEPRECATED')
args = parser.parse_args() args = parser.parse_args()
args_defaults = parser.parse_args([]) args_defaults = parser.parse_args([])
@ -215,7 +215,7 @@ for arg in sys.argv[1:]:
if hasattr(args, arg): if hasattr(args, arg):
provided_arguments.append(arg) provided_arguments.append(arg)
deprecated_args = ['tensorcores'] deprecated_args = []
def do_cmd_flags_warnings(): def do_cmd_flags_warnings():

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@ -103,6 +103,7 @@ def list_model_elements():
'logits_all', 'logits_all',
'no_offload_kqv', 'no_offload_kqv',
'row_split', 'row_split',
'tensorcores',
'streaming_llm', 'streaming_llm',
'attention_sink_size', 'attention_sink_size',
'hqq_backend', 'hqq_backend',

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@ -119,6 +119,7 @@ def create_ui():
shared.gradio['use_double_quant'] = gr.Checkbox(label="use_double_quant", value=shared.args.use_double_quant) 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['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['auto_devices'] = gr.Checkbox(label="auto-devices", value=shared.args.auto_devices) 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['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['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['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.') 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.')

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@ -58,6 +58,32 @@ def is_x86_64():
return platform.machine() == "x86_64" return platform.machine() == "x86_64"
def cpu_has_avx2():
try:
import cpuinfo
info = cpuinfo.get_cpu_info()
if 'avx2' in info['flags']:
return True
else:
return False
except:
return True
def cpu_has_amx():
try:
import cpuinfo
info = cpuinfo.get_cpu_info()
if 'amx' in info['flags']:
return True
else:
return False
except:
return True
def torch_version(): def torch_version():
site_packages_path = None site_packages_path = None
for sitedir in site.getsitepackages(): for sitedir in site.getsitepackages():
@ -279,7 +305,7 @@ def install_webui():
# Install Git and then Pytorch # Install Git and then Pytorch
print_big_message("Installing PyTorch.") print_big_message("Installing PyTorch.")
run_cmd(f"conda install -y -k ninja git && {install_pytorch}", assert_success=True, environment=True) run_cmd(f"conda install -y -k ninja git && {install_pytorch} && python -m pip install py-cpuinfo==9.0.0", assert_success=True, environment=True)
if selected_gpu == "INTEL": if selected_gpu == "INTEL":
# Install oneAPI dependencies via conda # Install oneAPI dependencies via conda
@ -346,13 +372,13 @@ def update_requirements(initial_installation=False, pull=True):
is_cpu = '+cpu' in torver # 2.0.1+cpu is_cpu = '+cpu' in torver # 2.0.1+cpu
if is_rocm: if is_rocm:
base_requirements = "requirements_amd.txt" base_requirements = "requirements_amd" + ("_noavx2" if not cpu_has_avx2() else "") + ".txt"
elif is_cpu or is_intel: elif is_cpu or is_intel:
base_requirements = "requirements_cpu_only.txt" base_requirements = "requirements_cpu_only" + ("_noavx2" if not cpu_has_avx2() else "") + ".txt"
elif is_macos(): elif is_macos():
base_requirements = "requirements_apple_" + ("intel" if is_x86_64() else "silicon") + ".txt" base_requirements = "requirements_apple_" + ("intel" if is_x86_64() else "silicon") + ".txt"
else: else:
base_requirements = "requirements.txt" base_requirements = "requirements" + ("_noavx2" if not cpu_has_avx2() else "") + ".txt"
requirements_file = base_requirements requirements_file = base_requirements
@ -363,7 +389,6 @@ def update_requirements(initial_installation=False, pull=True):
textgen_requirements = open(requirements_file).read().splitlines() textgen_requirements = open(requirements_file).read().splitlines()
if is_cuda118: if is_cuda118:
textgen_requirements = [req.replace('+cu121', '+cu118').replace('+cu122', '+cu118') for req in textgen_requirements] textgen_requirements = [req.replace('+cu121', '+cu118').replace('+cu122', '+cu118') for req in textgen_requirements]
textgen_requirements = [req for req in textgen_requirements if '-cu121' not in req]
if is_windows() and is_cuda118: # No flash-attention on Windows for CUDA 11 if is_windows() and is_cuda118: # No flash-attention on Windows for CUDA 11
textgen_requirements = [req for req in textgen_requirements if 'oobabooga/flash-attention' not in req] textgen_requirements = [req for req in textgen_requirements if 'oobabooga/flash-attention' not in req]

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@ -33,11 +33,23 @@ flask_cloudflared==0.0.14
sse-starlette==1.6.5 sse-starlette==1.6.5
tiktoken tiktoken
# llama-cpp-python (CUDA) # llama-cpp-python (CPU only, AVX2)
https://github.com/abetlen/llama-cpp-python/releases/download/v0.2.64-cu121/llama_cpp_python-0.2.64-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-0.2.65+cpuavx2-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
https://github.com/abetlen/llama-cpp-python/releases/download/v0.2.64-cu121/llama_cpp_python-0.2.64-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-0.2.65+cpuavx2-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
https://github.com/abetlen/llama-cpp-python/releases/download/v0.2.64-cu121/llama_cpp_python-0.2.64-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-0.2.65+cpuavx2-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
https://github.com/abetlen/llama-cpp-python/releases/download/v0.2.64-cu121/llama_cpp_python-0.2.64-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-0.2.65+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-0.2.65+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-0.2.65+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-0.2.65+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-0.2.65+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-0.2.65+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-0.2.65+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-0.2.65+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-0.2.65+cu121-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
# CUDA wheels # CUDA wheels
https://github.com/jllllll/AutoGPTQ/releases/download/v0.6.0/auto_gptq-0.6.0+cu121-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11" https://github.com/jllllll/AutoGPTQ/releases/download/v0.6.0/auto_gptq-0.6.0+cu121-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"

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@ -31,13 +31,15 @@ flask_cloudflared==0.0.14
sse-starlette==1.6.5 sse-starlette==1.6.5
tiktoken tiktoken
# llama-cpp-python (CPU only) # llama-cpp-python (CPU only, AVX2)
https://github.com/abetlen/llama-cpp-python/releases/download/v0.2.64/llama_cpp_python-0.2.64-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-0.2.65+cpuavx2-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
https://github.com/abetlen/llama-cpp-python/releases/download/v0.2.64/llama_cpp_python-0.2.64-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-0.2.65+cpuavx2-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
https://github.com/abetlen/llama-cpp-python/releases/download/v0.2.64/llama_cpp_python-0.2.64-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-0.2.65+cpuavx2-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
https://github.com/abetlen/llama-cpp-python/releases/download/v0.2.64/llama_cpp_python-0.2.64-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-0.2.65+cpuavx2-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
# AMD wheels # AMD wheels
https://github.com/oobabooga/llama-cpp-python-cuBLAS-wheels/releases/download/rocm/llama_cpp_python_cuda-0.2.65+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-0.2.65+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/jllllll/AutoGPTQ/releases/download/v0.6.0/auto_gptq-0.6.0+rocm5.6-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11" https://github.com/jllllll/AutoGPTQ/releases/download/v0.6.0/auto_gptq-0.6.0+rocm5.6-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
https://github.com/jllllll/AutoGPTQ/releases/download/v0.6.0/auto_gptq-0.6.0+rocm5.6-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10" https://github.com/jllllll/AutoGPTQ/releases/download/v0.6.0/auto_gptq-0.6.0+rocm5.6-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
https://github.com/turboderp/exllamav2/releases/download/v0.0.19/exllamav2-0.0.19+rocm5.6-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11" https://github.com/turboderp/exllamav2/releases/download/v0.0.19/exllamav2-0.0.19+rocm5.6-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"

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@ -0,0 +1,49 @@
accelerate==0.27.*
colorama
datasets
einops
gradio==4.26.*
hqq==0.1.5
jinja2==3.1.2
lm_eval==0.3.0
markdown
numba==0.59.*
numpy==1.26.*
optimum==1.17.*
pandas
peft==0.8.*
Pillow>=9.5.0
psutil
pyyaml
requests
rich
safetensors==0.4.*
scipy
sentencepiece
tensorboard
transformers==4.40.*
tqdm
wandb
# API
SpeechRecognition==3.10.0
flask_cloudflared==0.0.14
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-0.2.65+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-0.2.65+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-0.2.65+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-0.2.65+cpuavx-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
# AMD wheels
https://github.com/jllllll/AutoGPTQ/releases/download/v0.6.0/auto_gptq-0.6.0+rocm5.6-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
https://github.com/jllllll/AutoGPTQ/releases/download/v0.6.0/auto_gptq-0.6.0+rocm5.6-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
https://github.com/turboderp/exllamav2/releases/download/v0.0.19/exllamav2-0.0.19+rocm5.6-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
https://github.com/turboderp/exllamav2/releases/download/v0.0.19/exllamav2-0.0.19+rocm5.6-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
https://github.com/turboderp/exllamav2/releases/download/v0.0.19/exllamav2-0.0.19-py3-none-any.whl; platform_system != "Darwin" and platform_machine != "x86_64"
https://github.com/jllllll/GPTQ-for-LLaMa-CUDA/releases/download/0.1.1/gptq_for_llama-0.1.1+rocm5.6-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
https://github.com/jllllll/GPTQ-for-LLaMa-CUDA/releases/download/0.1.1/gptq_for_llama-0.1.1+rocm5.6-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
https://github.com/casper-hansen/AutoAWQ/releases/download/v0.2.3/autoawq-0.2.3+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/v0.2.3/autoawq-0.2.3+rocm561-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"

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@ -32,10 +32,10 @@ sse-starlette==1.6.5
tiktoken tiktoken
# Mac wheels # Mac wheels
https://github.com/abetlen/llama-cpp-python/releases/download/v0.2.64-metal/llama_cpp_python-0.2.64-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-0.2.65-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/abetlen/llama-cpp-python/releases/download/v0.2.64-metal/llama_cpp_python-0.2.64-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-0.2.65-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/abetlen/llama-cpp-python/releases/download/v0.2.64-metal/llama_cpp_python-0.2.64-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-0.2.65-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/abetlen/llama-cpp-python/releases/download/v0.2.64-metal/llama_cpp_python-0.2.64-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-0.2.65-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/abetlen/llama-cpp-python/releases/download/v0.2.64-metal/llama_cpp_python-0.2.64-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-0.2.65-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/abetlen/llama-cpp-python/releases/download/v0.2.64-metal/llama_cpp_python-0.2.64-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/llama-cpp-python-cuBLAS-wheels/releases/download/metal/llama_cpp_python-0.2.65-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/turboderp/exllamav2/releases/download/v0.0.19/exllamav2-0.0.19-py3-none-any.whl https://github.com/turboderp/exllamav2/releases/download/v0.0.19/exllamav2-0.0.19-py3-none-any.whl

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@ -32,12 +32,12 @@ sse-starlette==1.6.5
tiktoken tiktoken
# Mac wheels # Mac wheels
https://github.com/abetlen/llama-cpp-python/releases/download/v0.2.64-metal/llama_cpp_python-0.2.64-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-0.2.65-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/abetlen/llama-cpp-python/releases/download/v0.2.64-metal/llama_cpp_python-0.2.64-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-0.2.65-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/abetlen/llama-cpp-python/releases/download/v0.2.64-metal/llama_cpp_python-0.2.64-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-0.2.65-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/abetlen/llama-cpp-python/releases/download/v0.2.64-metal/llama_cpp_python-0.2.64-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-0.2.65-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/abetlen/llama-cpp-python/releases/download/v0.2.64-metal/llama_cpp_python-0.2.64-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-0.2.65-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/abetlen/llama-cpp-python/releases/download/v0.2.64-metal/llama_cpp_python-0.2.64-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-0.2.65-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/abetlen/llama-cpp-python/releases/download/v0.2.64-metal/llama_cpp_python-0.2.64-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-0.2.65-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/abetlen/llama-cpp-python/releases/download/v0.2.64-metal/llama_cpp_python-0.2.64-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/llama-cpp-python-cuBLAS-wheels/releases/download/metal/llama_cpp_python-0.2.65-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/turboderp/exllamav2/releases/download/v0.0.19/exllamav2-0.0.19-py3-none-any.whl https://github.com/turboderp/exllamav2/releases/download/v0.0.19/exllamav2-0.0.19-py3-none-any.whl

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@ -31,8 +31,8 @@ flask_cloudflared==0.0.14
sse-starlette==1.6.5 sse-starlette==1.6.5
tiktoken tiktoken
# llama-cpp-python (CPU only) # llama-cpp-python (CPU only, AVX2)
https://github.com/abetlen/llama-cpp-python/releases/download/v0.2.64/llama_cpp_python-0.2.64-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-0.2.65+cpuavx2-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
https://github.com/abetlen/llama-cpp-python/releases/download/v0.2.64/llama_cpp_python-0.2.64-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-0.2.65+cpuavx2-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
https://github.com/abetlen/llama-cpp-python/releases/download/v0.2.64/llama_cpp_python-0.2.64-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-0.2.65+cpuavx2-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
https://github.com/abetlen/llama-cpp-python/releases/download/v0.2.64/llama_cpp_python-0.2.64-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-0.2.65+cpuavx2-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"

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@ -0,0 +1,38 @@
accelerate==0.27.*
colorama
datasets
einops
gradio==4.26.*
hqq==0.1.5
jinja2==3.1.2
lm_eval==0.3.0
markdown
numba==0.59.*
numpy==1.26.*
optimum==1.17.*
pandas
peft==0.8.*
Pillow>=9.5.0
psutil
pyyaml
requests
rich
safetensors==0.4.*
scipy
sentencepiece
tensorboard
transformers==4.40.*
tqdm
wandb
# API
SpeechRecognition==3.10.0
flask_cloudflared==0.0.14
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-0.2.65+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-0.2.65+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-0.2.65+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-0.2.65+cpuavx-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"

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accelerate==0.27.*
aqlm[gpu,cpu]==1.1.3; platform_system == "Linux"
bitsandbytes==0.43.*
colorama
datasets
einops
gradio==4.26.*
hqq==0.1.5
jinja2==3.1.2
lm_eval==0.3.0
markdown
numba==0.59.*
numpy==1.26.*
optimum==1.17.*
pandas
peft==0.8.*
Pillow>=9.5.0
psutil
pyyaml
requests
rich
safetensors==0.4.*
scipy
sentencepiece
tensorboard
transformers==4.40.*
tqdm
wandb
# API
SpeechRecognition==3.10.0
flask_cloudflared==0.0.14
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-0.2.65+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-0.2.65+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-0.2.65+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-0.2.65+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-0.2.65+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-0.2.65+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-0.2.65+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-0.2.65+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-0.2.65+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-0.2.65+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-0.2.65+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-0.2.65+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/jllllll/AutoGPTQ/releases/download/v0.6.0/auto_gptq-0.6.0+cu121-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
https://github.com/jllllll/AutoGPTQ/releases/download/v0.6.0/auto_gptq-0.6.0+cu121-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
https://github.com/jllllll/AutoGPTQ/releases/download/v0.6.0/auto_gptq-0.6.0+cu121-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
https://github.com/jllllll/AutoGPTQ/releases/download/v0.6.0/auto_gptq-0.6.0+cu121-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
https://github.com/turboderp/exllamav2/releases/download/v0.0.19/exllamav2-0.0.19+cu121-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
https://github.com/turboderp/exllamav2/releases/download/v0.0.19/exllamav2-0.0.19+cu121-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
https://github.com/turboderp/exllamav2/releases/download/v0.0.19/exllamav2-0.0.19+cu121-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
https://github.com/turboderp/exllamav2/releases/download/v0.0.19/exllamav2-0.0.19+cu121-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
https://github.com/turboderp/exllamav2/releases/download/v0.0.19/exllamav2-0.0.19-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/jllllll/GPTQ-for-LLaMa-CUDA/releases/download/0.1.1/gptq_for_llama-0.1.1+cu121-cp311-cp311-win_amd64.whl; platform_system == "Windows" and python_version == "3.11"
https://github.com/jllllll/GPTQ-for-LLaMa-CUDA/releases/download/0.1.1/gptq_for_llama-0.1.1+cu121-cp310-cp310-win_amd64.whl; platform_system == "Windows" and python_version == "3.10"
https://github.com/jllllll/GPTQ-for-LLaMa-CUDA/releases/download/0.1.1/gptq_for_llama-0.1.1+cu121-cp311-cp311-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.11"
https://github.com/jllllll/GPTQ-for-LLaMa-CUDA/releases/download/0.1.1/gptq_for_llama-0.1.1+cu121-cp310-cp310-linux_x86_64.whl; platform_system == "Linux" and platform_machine == "x86_64" and python_version == "3.10"
autoawq==0.2.3; platform_system == "Linux" or platform_system == "Windows"