Update an artifact - Weights & Biases Documentation

Pass desired values to update the description, metadata, and alias of an artifact. Update a run previously logged to W&B with the W&B Public API with (wandb.Api). Use wandb.Run.save() to update an artifact when is first initialized and still active.

When to use wandb.Artifact.save() or wandb.Run.log_artifact()

Use Artifact.save() to update an existing artifact without starting a new run.
Use wandb.Run.log_artifact() to create a new artifact and associate it with a specific run.

Use the W&B Public API (wandb.Api) to update an artifact. Use the wandb.Artifact (wandb.Artifact) Class while a run is active.

You can not update the alias of artifact linked to a model in Model Registry.

During a run
W&B Public API
With collections

The following code example demonstrates how to update the description of an artifact using the wandb.Artifact API:

import wandb

with wandb.init(project="<example>") as run:
    artifact = run.use_artifact("<artifact-name>:<alias>")
    artifact.description = "<description>"
    artifact.save()

The following example updates an artifact with wandb.Api:

import wandb

api = wandb.Api()

artifact = api.artifact("entity/project/artifact:alias")

# Update the description
artifact.description = "My new description"

# Selectively update metadata keys
artifact.metadata["oldKey"] = "new value"

# Replace the metadata entirely
artifact.metadata = {"newKey": "new value"}

# Add an alias
artifact.aliases.append("best")

# Remove an alias
artifact.aliases.remove("latest")

# Completely replace the aliases
artifact.aliases = ["replaced"]

# Persist all artifact modifications
artifact.save()

For more information, see the Weights and Biases Artifact API.

You can also update an Artifact collection in the same way as a singular artifact:

import wandb
with wandb.init(project="<example>") as run:
    api = wandb.Api()
    artifact = api.artifact_collection(type="<type-name>", collection="<collection-name>")
    artifact.name = "<new-collection-name>"
    artifact.description = "<This is where you'd describe the purpose of your collection.>"
    artifact.save()

For more information, see the Artifacts Collection reference.