Stars
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Models and examples built with TensorFlow
Robust Speech Recognition via Large-Scale Weak Supervision
🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), ga…
TensorFlow code and pre-trained models for BERT
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (V…
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
Code and documentation to train Stanford's Alpaca models, and generate the data.
Instant voice cloning by MIT and MyShell.
Glances an Eye on your system. A top/htop alternative for GNU/Linux, BSD, Mac OS and Windows operating systems.
Image-to-Image Translation in PyTorch
Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.
Graph Neural Network Library for PyTorch
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
Open standard for machine learning interoperability
PyTorch implementations of Generative Adversarial Networks.
State-of-the-Art Text Embeddings
An open-source NLP research library, built on PyTorch.
A PyTorch implementation of the Transformer model in "Attention is All You Need".
Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
tensorboard for pytorch (and chainer, mxnet, numpy, ...)
A Python implementation of global optimization with gaussian processes.
Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.
Open Source Neural Machine Translation and (Large) Language Models in PyTorch
XLNet: Generalized Autoregressive Pretraining for Language Understanding
Google AI 2018 BERT pytorch implementation
Code for the paper "Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer"