danijar/ninjax
General Modules for JAX
This tool helps machine learning engineers and researchers build and manage complex deep learning models using JAX. It provides a flexible way to define neural network layers and other components, explicitly controlling how internal parameters and temporary data are updated. You feed it your JAX-based model definitions, and it outputs a more modular and controllable model structure, making it easier to manage stateful components and integrate different JAX libraries.
Available on PyPI.
Use this if you are a machine learning engineer or researcher developing advanced JAX-based models and need fine-grained control over module state, parameters, and optimizer buffers.
Not ideal if you are looking for a high-level, opinionated deep learning framework that handles most state management automatically.
Stars
72
Forks
2
Language
Python
License
MIT
Category
Last pushed
Feb 21, 2026
Commits (30d)
0
Dependencies
1
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