Hugging Face Space Deployer

Create, configure, and deploy interactive ML demos on Hugging Face Spaces.

Deployment fails in predictable ways when the model's type is misidentified. Always analyze the model before generating any code.

Workflow

1. Analyze the model — full model, LoRA adapter, or Inference API supported.
2. Choose a deployment strategy from that analysis.
3. Ask the user if the model type or cost preference is unclear.
4. Deploy with scripts/deploy_model.py, or assemble the Space manually.
5. Set the runtime hardware in Space Settings.
6. Verify the Space builds and actually answers a request.

Step 1: Analyze the model

Inspect the model's files on the Hub before anything else: