# Fine-Tuning Pipeline

For developers who need domain-specific models but do not have the infrastructure to train them:

1. Select a base model from the Cluster catalog
2. Provide training data (upload directly or reference an existing tokenized dataset)
3. Configure parameters (learning rate, epochs, batch size, evaluation split)
4. Submit the fine-tuning job
5. Cluster provisions compute, runs training, and evaluates the result
6. The fine-tuned model is deployed to the inference API automatically

The output is a live endpoint, not a file. The model is immediately callable by the developer and, optionally, by any other user on the platform.


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://cluster-protocol.gitbook.io/whitepaper/custom-model-hosting-and-fine-tuning/fine-tuning-pipeline.md?ask=<question>
```

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Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.