Add a model

You can add models from any ML project to the model registry. To add a model to your model registry, Iterative Studio creates an annotation for it in an artifacts.yaml file in your Git repository. If you are using the GTO command line tool, you can also add models from the CLI. To add models using Iterative Studio, watch this tutorial video or read on below:

1. Click on Add a model.

2. Select a connected repository to which you want to add the model.

   If your model file or the .dvc file for your model already exists in a Git repo, select that repo. If your model file resides in remote storage (S3, GCS, etc.), select the Git repo where you want to add the model.

3. Enter the path of the model file as follows:

   • If the model file is in the Git repository, enter the relative path of the model (from the repository root).
   • If the model file is in remote storage but is DVC-tracked, enter the project path of the corresponding .dvc file.
   • If the model file is in remote storage and is not DVC-tracked, enter the absolute path of the model file.
   • If you use MLEM to save your model, use the path to the binary file that MLEM generates. After you have run mlem init, Iterative Studio will be able to parse the .mlem file to extract model metadata.

   If the path you entered is a cloud path, Iterative Studio will ask you for the repository path where the dvc reference to the model should be saved.

4. Provide labels for your model. For example, if your model is about reviewing sentiment analysis using natural language processing, one of the labels may be nlp. You can provide multiple labels as a comma separated list. Eg, nlp, sentiment_analysis.

5. Optionally, add a brief description for your model.

6. Enter a Git commit message. Then, select the branch to commit to. You can commit to either the base branch or a new branch. Iterative Studio will commit the changes to the selected branch. If you commit to a new branch, Iterative Studio will also create a Git pull request from the new branch to the base branch.

7. Now, click on Commit changes.

8. At this point, the new model appears in the models dashboard.

9. In your Git repository, you will find that an entry for the new model has been created in the artifacts.yaml file in the repository's root. If you had committed to a new branch, a new pull request (or merge request in the case of GitLab) will also have been created to merge the new branch into the base branch.

10. If you had added a model from a cloud storage, the following will also happen before the commit is created:

• If the repository does not contain DVC, Iterative Studio will run dvc init. It is needed to version the model in the git repository. Learn more.
• If the specified directory does not exist yet, it will be created.
• Iterative Studio will import the model to the repository by executing dvc import-url <remote_path> <directory_path>/<filename from remote_path> --no-exec.
• Iterative Studio annotate the model by executing gto annotate <model_name> --path <directory_path>/<filename from remote_path> --type model. Learn more.