Stars
🤗 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.
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Models and examples built with TensorFlow
A high-throughput and memory-efficient inference and serving engine for LLMs
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
TensorFlow code and pre-trained models for BERT
🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch.
Generative Models by Stability AI
Fully open reproduction of DeepSeek-R1
Official inference repo for FLUX.1 models
Code for the paper "Language Models are Unsupervised Multitask Learners"
Graph Neural Network Library for PyTorch
Fast and memory-efficient exact attention
Universal LLM Deployment Engine with ML Compilation
Ongoing research training transformer models at scale
Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
Python package built to ease deep learning on graph, on top of existing DL frameworks.
Replace 'hub' with 'ingest' in any GitHub URL to get a prompt-friendly extract of a codebase
An open source implementation of CLIP.
A PyTorch Extension: Tools for easy mixed precision and distributed training in Pytorch
Web mining module for Python, with tools for scraping, natural language processing, machine learning, network analysis and visualization.
Google AI 2018 BERT pytorch implementation
A system for quickly generating training data with weak supervision
Transformer: PyTorch Implementation of "Attention Is All You Need"
g1: Using Llama-3.1 70b on Groq to create o1-like reasoning chains
A bootloader and experimentation playground for Apple Silicon