A simple ML model versioning tool
Project description
MLSaver
MLSaver is a lightweight Python package that lets you version-control your machine learning models locally — similar to Git, but for ML experiments.
✨ Features
- Save trained models with simple commands
- Load previous model versions instantly
- List all saved versions
- Delete unwanted versions
- Prints model info
- Works locally — no extra setup, no cloud required
🧠 Installation
pip install MLSaver
⚙️ Importing MLSaver
Import the class into your project:
from mlsaver import MLSaver
Then create an instance:
saver = MLSaver()
⚙️ Methods
| Method | Description | Example |
|---|---|---|
commit(model, "v1") |
Save a trained model with a version name. | saver.commit(model, "v1") |
checkout("v1") |
Load a previously saved model. | model = saver.checkout("v1") |
log() |
List all saved versions. | saver.log() |
delete("v1") |
Delete a saved version. | saver.delete("v1") |
rename("v1", "v1_fixed") |
Rename an existing version. | saver.rename("v1", "v1_fixed") |
info("v1") |
Show detailed info about a version (size, date, hyperparameters). | saver.info("v1") |
clear() |
Delete all saved versions (with confirmation). | saver.clear() |
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