Grow your team on GitHub
GitHub is home to over 50 million developers working together. Join them to grow your own development teams, manage permissions, and collaborate on projects.
Sign up
Pinned repositories
Repositories
-
text-to-text-transfer-transformer
Code for the paper "Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer"
-
-
bleurt
BLEURT is a metric for Natural Language Generation based on transfer learning.
-
dex-lang
Research language for array processing in the Haskell/ML family
-
meta-dataset
A dataset of datasets for learning to learn from few examples
-
xtreme
XTREME is a benchmark for the evaluation of the cross-lingual generalization ability of pre-trained multilingual models that covers 40 typologically diverse languages and includes nine tasks.
-
arxiv-latex-cleaner
arXiv LaTeX Cleaner: Easily clean the LaTeX code of your paper to submit to arXiv
-
electra
ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators
-
computation-thru-dynamics
Understanding computation in artificial and biological recurrent networks through the lens of dynamical systems.
-
tiny-differentiable-simulator
Tiny Differentiable Simulator is a header-only C++ physics library with zero dependencies.
-
turkish-morphology
A two-level morphological analyzer for Turkish.
-
tensor2robot
Distributed machine learning infrastructure for large-scale robotics research
-
morph-net
Fast & Simple Resource-Constrained Learning of Deep Network Structure
-
simclr
SimCLR - A Simple Framework for Contrastive Learning of Visual Representations
-
ssl_detection
Semi-supervised learning for object detection
-
batch_rl
Offline Reinforcement Learning (aka Batch Reinforcement Learning) on Atari 2600 games
-
language
Shared repository for open-sourced projects from the Google AI Language team.
-
motion_imitation
Code accompanying the paper "Learning Agile Robotic Locomotion Skills by Imitating Animals"
-
bert
TensorFlow code and pre-trained models for BERT
-
-
recsim
A Configurable Recommender Systems Simulation Platform
-
dads
Code for 'Dynamics-Aware Unsupervised Discovery of Skills' (DADS). Enables skill discovery without supervision, which can be combined with model-based control.