Starred repositories
A javascript text differencing implementation.
🌼 🌼 🌼 🌼 🌼 The most popular, free and open-source Tailwind CSS component library
AI Infra 全栈从0入门学习资料：https://caomaolufei.github.io/AIInfraGuide/
TokenSpeed is a speed-of-light LLM inference engine.
A single CLAUDE.md file to improve Claude Code behavior, derived from Andrej Karpathy's observations on LLM coding pitfalls.
A safetensors extension to efficiently store sparse quantized tensors on disk
An agentic skills framework & software development methodology that works.
You can monitor the usage of cursor and set a threshold. When the usage exceeds the threshold, a warning will pop up.
Conditional Memory via Scalable Lookup: A New Axis of Sparsity for Large Language Models
agent-sandbox enables easy management of isolated, stateful, singleton workloads, ideal for use cases like AI agent runtimes.
Offline optimization of your disaggregated Dynamo graph
LeaderWorkerSet: An API for deploying a group of pods as a unit of replication
A framework for efficient model inference with omni-modality models
from MHA, MQA, GQA to MLA by 苏剑林, with code
Podman Desktop is the best free and open source tool to work with Containers and Kubernetes for developers. Get an intuitive and user-friendly interface to effortlessly build, manage, and deploy co…
LMCache: Supercharge Your LLM with the Fastest KV Cache Layer
KeePassXC is a cross-platform community-driven port of the Windows application “KeePass Password Safe”.
System Level Intelligent Router for Mixture-of-Models at Cloud, Data Center and Edge
AI 基础知识 - GPU 架构、CUDA 编程、大模型基础及AI Agent 相关知识。
KV cache store for distributed LLM inference
Super simple build framework with fast, repeatable builds and an instantly familiar syntax – like Dockerfile and Makefile had a baby.
OpenCompass is an LLM evaluation platform, supporting a wide range of models (Llama3, Mistral, InternLM2,GPT-4,LLaMa2, Qwen,GLM, Claude, etc) over 100+ datasets.
Unified Communication X (mailing list - https://elist.ornl.gov/mailman/listinfo/ucx-group)
My learning notes for ML SYS.