Create an artifact alias - Weights & Biases Documentation

Use aliases as pointers to specific versions. By default, wandb.Run.log_artifact() adds the latest alias to the logged version. W&B creates an artifact version v0 and attaches it to your artifact when you log that artifact for the first time. W&B checksums the contents when you log again to the same artifact. If the artifact changed, W&B saves a new version v1. For example, if you want your training script to pull the most recent version of a dataset, specify latest when you use that artifact. The following code example demonstrates how to download a recent dataset artifact named bike-dataset that has an alias, latest:

import wandb

with wandb.init(project="<project>") as run:
    artifact = run.use_artifact("bike-dataset:latest")
    artifact.download()

You can also apply a custom alias to an artifact version. For example, if you want to mark that model checkpoint is the best on the metric AP-50, you could add the string 'best-ap50' as an alias when you log the model artifact.

with wandb.init(project="<project>") as run:
    artifact = wandb.Artifact("run-3nq3ctyy-bike-model", type="model")
    artifact.add_file("model.h5")
    run.log_artifact(artifact, aliases=["latest", "best-ap50"])

Update an artifact

Create an artifact version

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