Popular GitHub Repositories for Heterogeneous Graph Transformer

? Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

??? 60+ Implementations/tutorials of deep learning papers with side-by-side notes ?; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), ? reinforcement learning (ppo, dqn), capsnet, distillation, ... ?

Implement a ChatGPT-like LLM in PyTorch from scratch, step by step

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

Port of OpenAI's Whisper model in C/C++

Making large AI models cheaper, faster and more accessible

The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more

OpenMMLab Detection Toolbox and Benchmark

Cross-platform, customizable ML solutions for live and streaming media.

Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch

Graph Neural Network Library for PyTorch

SOTA Open Source TTS

? A ranked list of awesome machine learning Python libraries. Updated weekly.

CVPR 2025 论文和开源项目合集

[NeurIPS 2022] Towards Robust Blind Face Restoration with Codebook Lookup Transformer

SGLang is a fast serving framework for large language models and vision language models.

Python SDK for Agent AI Observability, Monitoring and Evaluation Framework. Includes features like agent, llm and tools tracing, debugging multi-agentic system, self-hosted dashboard and advanced analytics with timeline and execution graph view

pix2tex: Using a ViT to convert images of equations into LaTeX code.

This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".

Natural Language Processing Tutorial for Deep Learning Researchers