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Importing a model brings external weights into your project so you can evaluate and deploy them just like a model trained in Oumi. You can pull from a HuggingFace repo or from a presigned S3 URL.

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WHEN TO IMPORT A MODEL

Import a model when you want to:
  • Evaluate an open-source or third-party model alongside your own
  • Deploy a model you trained outside of Oumi
  • Bring a fine-tuned checkpoint into a project to serve it

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HOW TO IMPORT A MODEL

  1. Go to the Models page.
  2. Click the More actions button (the three dots) at the top right.
  3. Choose Import from HuggingFace or Import from S3.
Import model menu

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Import from HuggingFace

Pull model weights from a HuggingFace Hub repo into your project.
  1. Enter a Display name for the model.
  2. Enter the Repo ID in org/repo format, for example meta-llama/Llama-3.2-1B.
  3. Set the Base model (see Set the base model).
  4. Click to start the import.
Import from HuggingFace
Only the repo’s default branch is imported. For gated or private repos, add a HuggingFace token to your project first so Oumi can access the weights.

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Import from S3

Pull a model artifact from a presigned S3 URL into your project.
  1. Enter a Display name for the model.
  2. Paste the Presigned URL to your model artifact.
  3. Set the Base model (see Set the base model).
  4. Click to start the import.
Import from S3
Treat the presigned URL as a secret. The signature grants direct read access to your file.
The URL can point to a single weight file or an archive (.zip, .tar, .tar.gz), up to 2 TB uncompressed and 100,000 files.

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SET THE BASE MODEL

The base model tells Oumi which model your weights derive from. Oumi uses it to apply the correct chat template and to enable accurate evaluation and deployment, so setting it right matters.
  • For HuggingFace imports, Oumi auto-detects the base model from the Repo ID. Leave it on Auto-detect unless your weights derive from a different model.
  • For S3 imports, set the base model yourself. Use the HuggingFace ID of the model your weights are based on, for example Qwen/Qwen3-0.6B.
  • If your base model isn’t in the list, choose Other and type its HuggingFace ID.
Set the base model
If you fine-tuned a model, the base model is the original model you started from, not your fine-tuned checkpoint.

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AFTER IMPORTING

HuggingFace and S3 imports run in the background. You’ll see a confirmation that the import has started, and the model appears on the Models page once it finishes. Larger models take longer to copy in.

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USING YOUR IMPORTED MODEL

Once imported, your model works anywhere a custom model does:

Run an evaluation

Select your imported model as the model under test and score it with your evaluators.

Deploy for inference

Serve your imported model as a live API endpoint with hosted inference.

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IMPORTING WITH THE OUMI AGENT

You can also import a model by asking the Oumi Agent. Tell it which model you want to bring in, for example “import meta-llama/Llama-3.2-1B from HuggingFace,” and the Agent walks you through the import and can continue straight into evaluation or deployment.