mmulet/jellyml
JellyML is an open-source tool (python API and command line) for effortlessly embedding a snapshot of your code into a checkpoint of a pytorch (and pytorch lightning) model.
JellyML helps machine learning developers maintain version control by embedding their code directly into PyTorch model checkpoints. This ensures that when a model checkpoint is loaded, the exact code used to create it is also available, simplifying model reproducibility and debugging. It's designed for machine learning engineers and researchers working with PyTorch models.
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Use this if you need to reliably link the specific code version with your PyTorch or PyTorch Lightning model checkpoints for better reproducibility and easier debugging.
Not ideal if you are looking for a general-purpose model versioning system that manages datasets, experiments, and model artifacts beyond just code embedding.
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Language
Pug
License
LGPL-3.0
Category
Last pushed
Jul 10, 2025
Commits (30d)
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