Stars
📚LeetCUDA: Modern CUDA Learn Notes with PyTorch for Beginners🐑, 200+ CUDA Kernels, Tensor Cores, HGEMM, FA-2 MMA.🎉
verl: Volcano Engine Reinforcement Learning for LLMs
A Next-Generation Training Engine Built for Ultra-Large MoE Models
Macro Placement - benchmarks, evaluators, and reproducible results from leading methods in open source
Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)
Fully open reproduction of DeepSeek-R1
This GitHub repo is for the OpenROAD and CircuitOps Tutorial at ASP-DAC 2024
OpenR: An Open Source Framework for Advanced Reasoning with Large Language Models
A collection of LLM papers, blogs, and projects, with a focus on OpenAI o1 🍓 and reasoning techniques.
An Easy-to-use, Scalable and High-performance Agentic RL Framework based on Ray (PPO & DAPO & REINFORCE++ & TIS & vLLM & Ray & Async RL)
LLMs and the Future of Chip Design: Unveiling Security Risks and Building Trust
Multilingual Voice Understanding Model
Production-ready platform for agentic workflow development.
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.
🤯 LobeHub - an open-source, modern design AI Agent Workspace. Supports multiple AI providers, Knowledge Base (file upload / RAG ), one click install MCP Marketplace and Artifacts / Thinking. One-cl…
A natural language interface for computers
CLI platform to experiment with codegen. Precursor to: https://lovable.dev
Interactive roadmaps, guides and other educational content to help developers grow in their careers.
2021 年成為 Web 開發人員的路線圖 台灣正體中文版
Website for the OpenROAD tutorial held at the MICRO 2022 conference
Easily turn large sets of image urls to an image dataset. Can download, resize and package 100M urls in 20h on one machine.
(ECCV 2024) Empowering Multimodal Large Language Model as a Powerful Data Generator
mPLUG-DocOwl: Modularized Multimodal Large Language Model for Document Understanding
Plumb a PDF for detailed information about each char, rectangle, line, et cetera — and easily extract text and tables.
Easily compute clip embeddings and build a clip retrieval system with them