The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

A game theoretic approach to explain the output of any machine learning model.

A simple screen parsing tool towards pure vision based GUI agent

Kolmogorov Arnold Networks

StableLM: Stability AI Language Models

The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery 🧑‍🔬

NVIDIA Isaac GR00T N1.6 - A Foundation Model for Generalist Robots.

Book about interpretable machine learning

SimCLRv2 - Big Self-Supervised Models are Strong Semi-Supervised Learners

An automatic evaluator for instruction-following language models. Human-validated, high-quality, cheap, and fast.

Unofficial implementation of the ImageNet, CIFAR 10 and SVHN Augmentation Policies learned by AutoAugment using pillow

A library for experimenting with, training and evaluating neural networks, with a focus on adversarial robustness.

(ICML'25 Outstanding) CollabLLM: From Passive Responders to Active Collaborators

[ICCV 2021] Aligning Latent and Image Spaces to Connect the Unconnectable

Improving Alignment and Robustness with Circuit Breakers

Implementation of Estimating Training Data Influence by Tracing Gradient Descent (NeurIPS 2020)

Pytorch implementation of Generative Models as Distributions of Functions 🌿

Official implementation of "MetaSDF: Meta-learning Signed Distance Functions"

Decomposing and Editing Predictions by Modeling Model Computation

Tools for training explainable models using attribution priors.

Differentiable Data Augmentation Library

Authors official implementation of "Big GANs Are Watching You" pre-print

Provably defending pretrained classifiers including the Azure, Google, AWS, and Clarifai APIs

Codebase for Learning Invariances in Neural Networks