🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.

Models and examples built with TensorFlow

scikit-learn: machine learning in Python

Deep Learning for humans

PyTorch Tutorial for Deep Learning Researchers

[NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.

Jupyter metapackage for installation and documentation

Denoising Diffusion Probabilistic Models

Code for the paper "Improved Techniques for Training GANs"

🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch

GANs with spectral normalization and projection discriminator

Noise Conditional Score Networks (NeurIPS 2019, Oral)

[CVPR 2020 Workshop] A PyTorch GAN library that reproduces research results for popular GANs.

PyTorch reimplementation of Diffusion Models

The official PyTorch implementation for NCSNv2 (NeurIPS 2020)

Code for our CVPR 2018 paper, "On the Robustness of Semantic Segmentation Models to Adversarial Attacks"

Agent with vision ability via llava & autogen

Pre-trained model, code, and materials from the paper "Impact of Adversarial Examples on Deep Learning Models for Biomedical Image Segmentation" (MICCAI 2019).

PyTorch implementation of Algorithm 1 of "On the Anatomy of MCMC-Based Maximum Likelihood Learning of Energy-Based Models"

StyleGAN2 but rewritten for TPUs.

PyTorch implementation of BPDA+EOT attack to evaluate adversarial defense with an EBM

Pytorch implementation with segmentation model and adversarial attacks

Code for reproducing the experiments in our work "EBM Life Cycle: MCMC Strategies for Synthesis, Defense, and Density Modeling".