# Train

- [Train a Model](https://docs.roboflow.com/train/train.md): Train a model using state-of-the-art technology in the Roboflow dashboard.
- [Train from a Universe Checkpoint](https://docs.roboflow.com/train/train/roboflow-universe-checkpoints.md): Start training from a checkpoint based on one of the 50,000+ trained models available on Roboflow Universe.
- [Train from Azure Vision](https://docs.roboflow.com/train/train/pro-third-party-training-integrations.md): Train a model on Azure Vision and upload to Roboflow.
- [Train from Google Cloud](https://docs.roboflow.com/train/train/train-from-google-cloud.md): Train a model on Google Cloud and upload to Roboflow.
- [Training Resolutions by Model Type](https://docs.roboflow.com/train/training-resolutions-by-model-type.md)
- [Roboflow Instant](https://docs.roboflow.com/train/roboflow-instant.md): Train a few-shot model for use in building a Proof of Concept application with computer vision.
- [Cancel a Training Job](https://docs.roboflow.com/train/cancel-a-training-job.md): You can cancel a training job for any reason while a model is training.
- [Stop Training Early](https://docs.roboflow.com/train/stop-training-early.md): You can stop a training job early if your model has already converged.
- [View Training Results](https://docs.roboflow.com/train/training-results.md): Training graphs and insights are made available for all Roboflow Train jobs.
- [View Trained Models](https://docs.roboflow.com/train/view-trained-models.md): See all Instant and Roboflow Train models in your project.
- [Evaluate Trained Models](https://docs.roboflow.com/train/evaluate-trained-models.md): Use Model Evaluation to explore how your model performs on your test dataset.
- [Neural Architecture Search](https://docs.roboflow.com/train/neural-architecture-search.md): Automatically search for the optimal model architecture and fine tune your model simultaneously.


---

# 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://docs.roboflow.com/train.md?ask=<question>
```

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