Stars
This is the official repository for The Hundred-Page Language Models Book by Andriy Burkov
An Easy-to-use, Scalable and High-performance RLHF Framework based on Ray (PPO & GRPO & REINFORCE++ & LoRA & vLLM & RFT)
A very simple GRPO implement for reproducing r1-like LLM thinking.
Fully open reproduction of DeepSeek-R1
Transformer Explained Visually: Learn How LLM Transformer Models Work with Interactive Visualization
A latent text-to-image diffusion model
Open-Sora: Democratizing Efficient Video Production for All
This project aim to reproduce Sora (Open AI T2V model), we wish the open source community contribute to this project.
Large World Model -- Modeling Text and Video with Millions Context
Hackable and optimized Transformers building blocks, supporting a composable construction.
Free and Open Source, Distributed, RESTful Search Engine
Tutel MoE: Optimized Mixture-of-Experts Library, Support DeepSeek FP8/FP4
Transformer related optimization, including BERT, GPT
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (V…
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Face recognition with deep neural networks.
Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning …
Datasets, Transforms and Models specific to Computer Vision
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".
Style guides for Google-originated open-source projects
Google 开源项目风格指南 (中文版)
Official repository of OFA (ICML 2022). Paper: OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework