maodoudou168

maodoudou168's Stars

• AUTOMATIC1111/stable-diffusion-webui

  Stable Diffusion web UI

  Language:Python145k1.1k7.7k27.2k

• hpcaitech/ColossalAI

  Making large AI models cheaper, faster and more accessible

  Language:Python39k3841.7k4.3k

• vllm-project/vllm

  A high-throughput and memory-efficient inference and serving engine for LLMs

  Language:Python32.7k2715.8k5k

• mli/paper-reading

  深度学习经典、新论文逐段精读

  27.6k73402.5k

• Dao-AILab/flash-attention

  Fast and memory-efficient exact attention

  Language:Python14.8k1241.2k1.4k

• liguodongiot/llm-action

  本项目旨在分享大模型相关技术原理以及实战经验（大模型工程化、大模型应用落地）

  Language:HTML12.2k101231.3k

• TheLastBen/fast-stable-diffusion

  fast-stable-diffusion + DreamBooth

  Language:Python7.6k872.1k1.3k

• bitsandbytes-foundation/bitsandbytes

  Accessible large language models via k-bit quantization for PyTorch.

  Language:Python6.5k521.1k644

• microsoft/DeepSpeedExamples

  Example models using DeepSpeed

  Language:Python6.2k755431.1k

• AutoGPTQ/AutoGPTQ

  An easy-to-use LLMs quantization package with user-friendly apis, based on GPTQ algorithm.

  Language:Python4.6k31471490

• qwopqwop200/GPTQ-for-LLaMa

  4 bits quantization of LLaMA using GPTQ

  Language:Python3k42218460

• ai-forever/Kandinsky-2

  Kandinsky 2 — multilingual text2image latent diffusion model

  Language:Jupyter Notebook2.8k4988309

• mit-han-lab/llm-awq

  [MLSys 2024 Best Paper Award] AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration

  Language:Python2.6k24193216

• intel/neural-compressor

  SOTA low-bit LLM quantization (INT8/FP8/INT4/FP4/NF4) & sparsity; leading model compression techniques on TensorFlow, PyTorch, and ONNX Runtime

  Language:Python2.3k33209258

• siliconflow/onediff

  OneDiff: An out-of-the-box acceleration library for diffusion models.

  Language:Jupyter Notebook1.8k39463109

• horseee/Awesome-Efficient-LLM

  A curated list for Efficient Large Language Models

  Language:Python1.4k41499

• mit-han-lab/smoothquant

  [ICML 2023] SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models

  Language:Python1.3k2191151

• HuangOwen/Awesome-LLM-Compression

  Awesome LLM compression research papers and tools.

  1.3k42683

• RahulSChand/gpu_poor

  Calculate token/s & GPU memory requirement for any LLM. Supports llama.cpp/ggml/bnb/QLoRA quantization

  Language:JavaScript1.2k71660

• dafish-ai/NTU-Machine-learning

  **大学李宏毅老师机器学习

  Language:Jupyter Notebook989300384

• lcdevelop/MachineLearningCourse

  机器学习精简入门教程

  838951261

• horseee/DeepCache

  [CVPR 2024] DeepCache: Accelerating Diffusion Models for Free

  Language:Python825155239

• OpenGVLab/OmniQuant

  [ICLR2024 spotlight] OmniQuant is a simple and powerful quantization technique for LLMs.

  Language:Python743168556

• pytorch/PiPPy

  Pipeline Parallelism for PyTorch

  Language:Python7303726386

• SqueezeAILab/SqueezeLLM

  [ICML 2024] SqueezeLLM: Dense-and-Sparse Quantization

  Language:Python664182843

• moon-hotel/BertWithPretrained

  An implementation of the BERT model and its related downstream tasks based on the PyTorch framework

  Language:Python571521109

• 3DAgentWorld/Toolkit-for-Prompt-Compression

  Toolkit for Prompt Compression

  Language:Python244238

• nbasyl/LLM-FP4

  The official implementation of the EMNLP 2023 paper LLM-FP4

  Language:Python16951012

• Lisennlp/distributed_train_pytorch

  pytorch分布式训练，支持多机多卡，单机多卡。

  Language:Python401310

• zbwxp/Dynamic-Token-Pruning

  Official Pytorch implementation of Dynamic-Token-Pruning (ICCV2023)

  Language:Python19233