> For the complete documentation index, see [llms.txt](https://docs.segments.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.segments.ai/tutorials/model-assisted-labeling.md).

# Model-assisted labeling

One way to drastically speed up data labeling is by leveraging your machine learning models from the start. Instead of labeling the entire dataset manually, you can use a model to help you by iterating between image labeling and model training.

![](https://1553794111-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FHczBG7NHgAtEe4ql1rXH%2Fuploads%2FqzfwcvWj8y7MQGMgWt9w%2Fimage.png?alt=media\&token=4d235c99-60e0-4c99-bd13-0234ca50f24e)

Segments.ai makes it easy to set up such model-assisted workflows.

We have two interactive tutorials in the form of a Google Colab notebook:

* [Speed up your image segmentation workflow with model-assisted labeling](https://colab.research.google.com/github/segments-ai/fast-labeling-workflow/blob/master/demo.ipynb)
* [Fast point cloud labeling with model predictions](https://colab.research.google.com/drive/1ZgHiMeHNlEB5WFyw93EiRkMd-0jmb7f4)


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

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

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://docs.segments.ai/tutorials/model-assisted-labeling.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

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.
