ScottAlexanderCameron/Jynx
A neural network library written in jax
This library helps machine learning engineers or researchers quickly build and train neural networks using JAX. You provide your data and define your model's architecture using a collection of standard layers, then train it with the built-in `fit` function. The output is a trained neural network model ready for deployment or further experimentation.
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Use this if you are a machine learning engineer who needs to quickly prototype and train neural networks in JAX, valuing transparency and control over hidden abstractions.
Not ideal if you prefer a high-level API with many pre-built, complex models and extensive automated features, or if you are not familiar with JAX or Optax.
Stars
13
Forks
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Language
Python
License
MIT
Category
Last pushed
Feb 03, 2025
Commits (30d)
0
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