Stars
An opinionated list of awesome Python frameworks, libraries, software and resources.
AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
🦜🔗 The platform for reliable agents.
real time face swap and one-click video deepfake with only a single image
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A high-throughput and memory-efficient inference and serving engine for LLMs
Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)
CLI platform to experiment with codegen. Precursor to: https://lovable.dev
1 min voice data can also be used to train a good TTS model! (few shot voice cloning)
The simplest, fastest repository for training/finetuning medium-sized GPTs.
Fine-tuning & Reinforcement Learning for LLMs. 🦥 Train OpenAI gpt-oss, DeepSeek-R1, Qwen3, Gemma 3, TTS 2x faster with 70% less VRAM.
ChatGLM-6B: An Open Bilingual Dialogue Language Model | 开源双语对话语言模型
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!
An open platform for training, serving, and evaluating large language models. Release repo for Vicuna and Chatbot Arena.
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The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (V…
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
PyTorch Tutorial for Deep Learning Researchers
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
DSPy: The framework for programming—not prompting—language models
Code and documentation to train Stanford's Alpaca models, and generate the data.
Qwen3 is the large language model series developed by Qwen team, Alibaba Cloud.
[NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.
Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.
Universal LLM Deployment Engine with ML Compilation
Fast and memory-efficient exact attention