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Text Generation with Custom HuggingFace Model

This demo helps you learn about:

  • Launching a pre trained custom text generation HuggingFace model in a Seldon Pipeline

  • Sending a text input request to get a generated text prediction

The custom HuggingFace text generation model is based on the TinyStories-1M model in the HuggingFace hub.

Create a Seldon ML Pipeline

  1. In the Overview page click Create new deployment.

  2. Enter the deployment details as follows:

    • Name: hf-custom-tiny-stories

    • Namespace: seldon

  3. Configure the default predictor as follows:

    • Runtime: HuggingFace

    • Model Project: default

  4. Click Next for the remaining steps and click Launch.

When the deployment is launched successfully, the status of the deployment becomes Available.

  1. Click the hf-custom-tiny-stories deployment that you created.

  2. In the deployment Dashboard page , click Predict in the left pane.

  3. In the Predict REST API dialog, click Enter JSON and paste the following text:

Try other or try a larger-scale model. You can find one in gs://seldon-models/scv2/samples/mlserver_1.6.0/huggingface-text-gen-custom-gpt2. However, you may need to request more memory.

Type:
Seldon ML Pipeline
Model URI:
gs://seldon-models/scv2/samples/mlserver_1.6.0/huggingface-text-gen-custom-tiny-stories
  • Storage Secret: (leave blank/none)

  • Click Predict.
    {
      "inputs": [{
        "name": "args",
        "shape": [1],
        "datatype": "BYTES",
        "data": ["The brown fox jumped"]
      }]
    }

    Make Predictions

    Next steps

    demos
    Default predictor spec
    A screenshot showing the Predict page with the textarea pre-populated