A Jax based neural network library for research
Project description
fastax
Overview
fastax is a Deep Learning Library built on top of Google's JAX that tries to facilitate doing research by providing a combination of JAX's versatility with implementations of the most used neural networks layers and utilities.
More concrete information and naming
fastax is both a combination of fastai and JAX and fastai and stax:
- It is built on top of JAX and most of its original code comes from its Neural Network mini-library stax
- One of the long term goals of this library is implementing Jeremy Howard's fastai course "Deep Learning From the Foundations"
For more information visit https://github.com/joaogui1/fastax
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