# Data-to-Model Pipeline

The marketplace is not an isolated product — it feeds directly into the inference and fine-tuning layers.

A data creator uploads a dataset → tokenizes it as an NFT → the dataset is used to fine-tune a model on Cluster compute → the resulting fine-tuned model is deployed to the inference API → consumers call the model and the data creator earns from both the dataset purchase and the downstream model usage.

This creates a closed-loop value chain where data, compute, and inference are interconnected within a single platform, and value flows back to contributors at every stage.


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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:

```
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```

The question should be specific, self-contained, and written in natural language.
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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.