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LLM Transparency Tool (LLM-TT), an open-source interactive toolkit for analyzing internal workings of Transformer-based language models. *Check out demo at* https://huggingface.co/spaces/facebook/l…
A native, user-mode, multi-process, graphical debugger.
An extremely fast Python linter and code formatter, written in Rust.
An extremely fast Python package and project manager, written in Rust.
Analyzes resource usage and performance characteristics of running containers.
High Fidelity Detection Mechanism for RSC/Next.js RCE (CVE-2025-55182 & CVE-2025-66478)
Project IceStorm - Lattice iCE40 FPGAs Bitstream Documentation (Reverse Engineered)
AddressSanitizer, ThreadSanitizer, MemorySanitizer
SGLang is a high-performance serving framework for large language models and multimodal models.
A fast usermode x86 and x86-64 emulator for Arm64 Linux
Free, open source geoguessr alternative
Renderer for the harmony response format to be used with gpt-oss
Code for the paper "Language Models are Unsupervised Multitask Learners"
Ongoing Lean formalisation of the proof of Fermat's Last Theorem
A high-throughput and memory-efficient inference and serving engine for LLMs
A Curated List of Awesome Works in World Modeling, Aiming to Serve as a One-stop Resource for Researchers, Practitioners, and Enthusiasts Interested in World Modeling.
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, PyTorch, and Hugging Face libraries.
Sharing both practical insights and theoretical knowledge about LLM evaluation that we gathered while managing the Open LLM Leaderboard and designing lighteval!
Lighteval is your all-in-one toolkit for evaluating LLMs across multiple backends
Language modeling with linear-cost context
Use Claude Code as the foundation for coding infrastructure, allowing you to decide how to interact with the model while enjoying updates from Anthropic.
Navigate your code with search labels, enhanced character motions and Treesitter integration
This repo contains the source code for the paper "Evolution Strategies at Scale: LLM Fine-Tuning Beyond Reinforcement Learning"