Stars
User-friendly AI Interface (Supports Ollama, OpenAI API, ...)
This is the repository for the distill web framework
NdLinear by Ensemble is a drop-in PyTorch module that shrinks your models with no accuracy loss. It powers the Ensemble Platform—upload any model and get back a smaller, faster version, ready to de…
A library for mechanistic interpretability of GPT-style language models
🤗 smolagents: a barebones library for agents that think in code.
📄 Configuration files that enhance Cursor AI editor experience with custom rules and behaviors
An R package to interpret biological trends from DNA methylation data
Model Context Protocol Servers
Autonomous coding agent right in your IDE, capable of creating/editing files, executing commands, using the browser, and more with your permission every step of the way.
Agent Laboratory is an end-to-end autonomous research workflow meant to assist you as the human researcher toward implementing your research ideas
RWKV (pronounced RwaKuv) is an RNN with great LLM performance, which can also be directly trained like a GPT transformer (parallelizable). We are at RWKV-7 "Goose". So it's combining the best of RN…
Official PyTorch implementation of Learning to (Learn at Test Time): RNNs with Expressive Hidden States
Official implementation of Stochastic Taylor Derivative Estimator (STDE) NeurIPS2024
Objectron is a dataset of short, object-centric video clips. In addition, the videos also contain AR session metadata including camera poses, sparse point-clouds and planes. In each video, the came…
disentanglement_lib is an open-source library for research on learning disentangled representations.
Implementation of Nougat Neural Optical Understanding for Academic Documents
Ready-to-run Docker images containing Jupyter applications
Python scripts for machine learning interpretability methods
A PyTorch converter for SimCLR checkpoints
Contrastive Predictive Coding for Automatic Speaker Verification
[CVPR 2024] Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data. Foundation Model for Monocular Depth Estimation
A collection of infrastructure and tools for research in neural network interpretability.