[D] JAX vs PyTorch in 2023

• equinox

  31 1,809 9.2 Python

  Elegant easy-to-use neural networks + scientific computing in JAX. https://docs.kidger.site/equinox/

FWIW this worked for me. :D My full-time job is now writing JAX libraries at Google. Equinox for neural networks, Diffrax for differential equation solvers, etc.

• RL-X

  3 87 9.0 Python

  A framework for Reinforcement Learning research.

I have a lot of implementations of RL algorithms with Flax in my RL library. Maybe looking at the code could help you. https://github.com/nico-bohlinger/RL-X

• InfluxDB

  www.influxdata.com sponsored

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

• diffrax

  21 1,230 8.3 Python

  Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/

FWIW this worked for me. :D My full-time job is now writing JAX libraries at Google. Equinox for neural networks, Diffrax for differential equation solvers, etc.

• NeMo

  29 10,021 9.8 Python

  A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech)

  

Nowadays... bigger repos like https://github.com/NVIDIA/NeMo are all pytorch, lots of work also published by Meta and Microsoft is all torch. I check new work on GitHub all the time and I haven't seen a Tensorflow repo in years except one.

Suggest a related project