Stars
A toolkit for developing and comparing reinforcement learning algorithms.
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
A simple tool to update bib entries with their official information (e.g., DBLP or the ACL anthology).
Models, data loaders and abstractions for language processing, powered by PyTorch
This extension attempts to make Google Images look and feel like it did before they changed everything on August 6th, 2019.
Important paper implementations for Question Answering using PyTorch
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
🤗 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.
Simple and easily configurable grid world environments for reinforcement learning
Simple and easily configurable 3D FPS-game-like environments for reinforcement learning
Tools for using computer algebra systems to solve math problems step-by-step with reinforcement learning
C# Data Extraction for "Learning to Represent Edits"
Utilities used by the Deep Program Understanding team
Pull current and historical baseball statistics using Python (Statcast, Baseball Reference, FanGraphs)
Some examples trained on very reduced versions of the MNIST training set
µniverse: RL environments for HTML5 games
An open source project to document AI progress through data.
Code for the ACL 2017 paper "Get To The Point: Summarization with Pointer-Generator Networks"
Genetic Programming in Python, with a scikit-learn inspired API
Lightweight library to build and train neural networks in Theano
Torch implementation of seq2seq machine translation with GRU RNN and attention
Intel® Nervana™ reference deep learning framework committed to best performance on all hardware
🤖 GPU accelerated Neural networks in JavaScript for Browsers and Node.js
Clean implementation of feed forward neural networks
header only, dependency-free deep learning framework in C++14