Stars
User-friendly AI Interface (Supports Ollama, OpenAI API, ...)
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
MAGI-1: Autoregressive Video Generation at Scale
Production-ready, Light, Flexible and Extensible ASGI API framework | Effortlessly Build Performant APIs
KAG is a logical form-guided reasoning and retrieval framework based on OpenSPG engine and LLMs. It is used to build logical reasoning and factual Q&A solutions for professional domain knowledge ba…
An open protocol enabling communication and interoperability between opaque agentic applications.
"LightRAG: Simple and Fast Retrieval-Augmented Generation"
Asynchronous HTTP client/server framework for asyncio and Python
deepbeepmeep / Wan2GP
Forked from Wan-Video/Wan2.1Wan 2.1 for the GPU Poor
verl: Volcano Engine Reinforcement Learning for LLMs
🔥 A minimal training framework for scaling FLA models
📚LeetCUDA: Modern CUDA Learn Notes with PyTorch for Beginners🐑, 200+ CUDA/Tensor Cores Kernels, HGEMM, FA-2 MMA etc.🔥
APOLLO: SGD-like Memory, AdamW-level Performance
🚀 Efficient implementations of state-of-the-art linear attention models in Torch and Triton
The Prodigy optimizer and its variants for training neural networks.
"MiniRAG: Making RAG Simpler with Small and Free Language Models"
Prodigy and Schedule-Free, together at last.
Scalable RL solution for advanced reasoning of language models
Official PyTorch Implementation for Paper "No More Adam: Learning Rate Scaling at Initialization is All You Need"
Efficient Triton Kernels for LLM Training
An Easy-to-use, Scalable and High-performance RLHF Framework based on Ray (PPO & GRPO & REINFORCE++ & vLLM & RFT & Dynamic Sampling & Async Agent RL)
Official inference framework for 1-bit LLMs