Stars
Your own personal AI assistant. Any OS. Any Platform. The lobster way. 🦞
Compute substrate for AI agents: lightweight enough to live on your laptop, elastic enough to scale into the cloud and unleash unlimited resources.
All-in-One Sandbox for AI Agents that combines Browser, Shell, File, MCP and VSCode Server in a single Docker container.
A high-throughput and memory-efficient inference and serving engine for LLMs
verl/HybridFlow: A Flexible and Efficient RL Post-Training Framework
A simple, performant and scalable Jax LLM!
VeOmni: Scaling Any Modality Model Training with Model-Centric Distributed Recipe Zoo
Mirage Persistent Kernel: Compiling LLMs into a MegaKernel
NVIDIA Resiliency Extension is a python package for framework developers and users to implement fault-tolerant features. It improves the effective training time by minimizing the downtime due to fa…
Machine Learning Engineering Open Book
Resume builder for academics and engineers
Learn how to use CUA (our Computer Using Agent) via the API on multiple computer environments.
Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!
🦉 OWL: Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation
A high-performance distributed file system designed to address the challenges of AI training and inference workloads.
Qwen3-VL is the multimodal large language model series developed by Qwen team, Alibaba Cloud.
Course information for CS598-Topics in LLM Agents(25'Spring) under the direction of Prof. Jiaxuan You ( jiaxuan@illinois.edu ).
My learning notes for ML SYS.
🐫 CAMEL: The first and the best multi-agent framework. Finding the Scaling Law of Agents. https://www.camel-ai.org
SGLang is a high-performance serving framework for large language models and multimodal models.
The official Python SDK for Model Context Protocol servers and clients
Nova: High-speed recursive zero-knowledge arguments from folding schemes