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Create and manage tokens of AI Model Experiments

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Before creating a token, ensure you meet the following prerequisites:

To interact with an AI Model Experiments instance via the MLflow™ Python SDK or REST API, you must first generate an access token. These tokens provide a secure authentication method for connecting your local development environments or CI/CD pipelines to the server. Please note that each token is instance-specific and cannot be used to access multiple instances.

  1. On the sidebar click on AI Model Experiments.
  2. Click on the instance for which you like to create an auth token.
  3. On the left select Tracking tokens.
  4. On the top bar click on Create tracking token.
  5. Enter a Token name and optionally a Description and a Lifetime.
  6. Click on Save.
  7. Copy the generated token to a safe place.
  1. On the sidebar click on AI Model Experiments.
  2. Click on the instance for which you like to list the auth token.
  3. On the left select Tracking tokens to see a list of all auth tokens associated with the instance.
  4. Click on a token to see its details pane.
  1. On the sidebar click on AI Model Experiments.
  2. Click on the instance for which you like to update the auth token.
  3. On the left select Tracking tokens to see a list of all auth tokens associated with the instance.
  4. Click on a token to see its details pane.
  5. Modify the desired entry.
  6. Click on Save to update the token.
  1. On the sidebar click on AI Model Experiments.
  2. Click on the instance for which you like to delete the auth token.
  3. On the left select Tracking tokens to see a list of all auth tokens associated with the instance.
  4. Click on the token’s three dots button and then on Delete to open the delete pane.
  5. Enter the tokens’s name and click on Delete to finally delete the token.