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llm-d is a Kubernetes-native high-performance distributed LLM inference framework
From the Transistor to the Web Browser, a rough outline for a 12 week course
Sharing both practical insights and theoretical knowledge about LLM evaluation that we gathered while managing the Open LLM Leaderboard and designing lighteval!
Tool for generating high quality Synthetic datasets
Lightweight coding agent that runs in your terminal
Open source interpretability artefacts for R1.
Fine-tuning & Reinforcement Learning for LLMs. 🦥 Train Qwen3, Llama 4, DeepSeek-R1, Gemma 3, TTS 2x faster with 70% less VRAM.
The AI Browser Automation Framework
A system for agentic LLM-powered data processing and ETL
A collection of notebooks/recipes showcasing some fun and effective ways of using Claude.
Any model. Any hardware. Zero compromise. Built with @ziglang / @openxla / MLIR / @bazelbuild
A package for easily working with US and state metadata
The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery 🧑🔬
Streamlines and simplifies prompt design for both developers and non-technical users with a low code approach.
LLM-Merging: Building LLMs Efficiently through Merging
SakanaAI / DiscoPOP
Forked from luchris429/DiscoPOPCode for Discovering Preference Optimization Algorithms with and for Large Language Models
DSPy: The framework for programming—not prompting—language models
Cohere Toolkit is a collection of prebuilt components enabling users to quickly build and deploy RAG applications.
JailbreakBench: An Open Robustness Benchmark for Jailbreaking Language Models [NeurIPS 2024 Datasets and Benchmarks Track]
SWE-agent takes a GitHub issue and tries to automatically fix it, using your LM of choice. It can also be employed for offensive cybersecurity or competitive coding challenges. [NeurIPS 2024]
Development repository for the Triton language and compiler