flax VS jaxline

Compare flax vs jaxline and see what are their differences.

flax

Flax is a neural network library for JAX that is designed for flexibility. (by google)
Jax
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flax jaxline
10 1
5,520 144
5.1% 0.0%
9.7 5.1
3 days ago 5 months ago
Python Python
Apache License 2.0 Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

flax

Posts with mentions or reviews of flax. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-04-23.

jaxline

Posts with mentions or reviews of jaxline. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-09-23.

What are some alternatives?

When comparing flax and jaxline you can also consider the following projects:

dm-haiku - JAX-based neural network library

deepmind-research - This repository contains implementations and illustrative code to accompany DeepMind publications

Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration

trax - Trax — Deep Learning with Clear Code and Speed

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

Flux.jl - Relax! Flux is the ML library that doesn't make you tensor

objax

tf-transformers - State of the art faster Transformer with Tensorflow 2.0 ( NLP, Computer Vision, Audio ).

jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

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

captum - Model interpretability and understanding for PyTorch