---
updatedAt: 2025-06-17T21:18:19.000Z
agentTools:
  projectIndex: https://documentation.picsellia.com/llms.txt
---

# 6. Store new files

The final step is to store the *model files* generated during training as *Artifacts* of the Picsellia `Experiment`. This step is straightforward. Suppose you are saving your model in the .h5 format; you will first save it.

```python
# ...

model.save('weights.h5', save_format='h5')
```

Now you just have to add a line to store this weight file in your Picsellia `Experiment` with

```
# ...

model.save('weights.h5', save_format='h5')
experiment.store(name="model-weights", trained_model_path="weights.h5", zip=True)
```

<Image align="center" className="border" border={true} src="https://files.readme.io/7fd03b2-6.png" />

**Here it is 🚀🎉**

The adaptation of your *training script* to Picsellia is now complete!

To summarize, we have adapted the initial script to:

* Pull all necessary data to initialize the model training (`DatasetVersion`, config/weights files, parameters, etc.).
* Log metrics to the Picsellia `Experiment` during training through *callbacks*.
* Compute and log `Evaluation` on a specific test set on the Picsellia `Experiment`.
* Store the *model files* generated as *artifacts* on the Picsellia `Experiment`.

After running this training script on your infrastructure, the experiment can be considered complete and can be exported as a `ModelVersion` for future operations with Picsellia.

The final version of the script [is available here](https://documentation.picsellia.com/docs/final-script).