Lists (4)
Stars
Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!
An animation library to enhance "animate.css"
🍿 A cross-browser library of CSS animations. As easy to use as an easy thing.
Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models"
🧠 Large-scale transformer-based language modelling using 🤗 HuggingFace.
Machine Learning Engineering Open Book
Automatic GPU+CPU memory profiling, re-use and memory leaks detection using jupyter/ipython experiment containers
Open source core of Synergy, the cross-platform keyboard and mouse sharing tool (Windows, macOS, Linux)
My tools for the Slurm HPC workload manager
Manage all your WordPress 301 redirects and monitor 404 errors
🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.
Original Implementation of Prompt Tuning from Lester, et al, 2021
arXiv LaTeX Cleaner: Easily clean the LaTeX code of your paper to submit to arXiv
🦜🔗 Build context-aware reasoning applications
A framework for few-shot evaluation of language models.
OFRAK: unpack, modify, and repack binaries.
Audiocraft is a library for audio processing and generation with deep learning. It features the state-of-the-art EnCodec audio compressor / tokenizer, along with MusicGen, a simple and controllable…
The official Python library for the OpenAI API
The Pile dataset sorted by programming language
🤗 Evaluate: A library for easily evaluating machine learning models and datasets.
This repo includes ChatGPT prompt curation to use ChatGPT better.
Detect the programming language of a source code
Grammars written for ANTLR v4; expectation that the grammars are free of actions.
Quantus is an eXplainable AI toolkit for responsible evaluation of neural network explanations
🚀 A simple way to launch, train, and use PyTorch models on almost any device and distributed configuration, automatic mixed precision (including fp8), and easy-to-configure FSDP and DeepSpeed support
A repo for distributed training of language models with Reinforcement Learning via Human Feedback (RLHF)
MII makes low-latency and high-throughput inference possible, powered by DeepSpeed.