Access production-ready models#

This example illustrate how to download production-stage model files.

It assumes the following:

You use tags to indicate model stage.
The model binaries are stored in the "model/binary" field of a run.

To access and download model files based on their stage:

Initialize a project:
```
import neptune

project = neptune.init_project(
    project="workspace-name/project-name", # (1)! 
    mode="read-only",
)   
```
1. The full project name. For example, "ml-team/classification".
  - You can copy the name from the project details ( → Details & privacy)
  - You can also find a pre-filled project string in Experiments → Create a new run.

Fetch the experiments table as a pandas DataFrame and filter it for runs with the "production" tag:

runs_table_df = project.fetch_runs_table(
    tag=["production"],
    columns=[],
).to_pandas()

Download the files using the download() method:

for run_id in runs_table_df["sys/id"]:
    with neptune.init_run(with_id=run_id, mode="read-only") as run:
        run["model/binary"].download(f"{run_id}_model.pkl")

To stop the connection to Neptune and sync all data, call the stop() method:
```
project.stop()
```

Result: The model files are downloaded to the current working directory.