# Tutorials

Step-by-step tutorials to guide you through complete workflows, from data preparation to serving trained models in production.

## [Train a Speculator](train.md)

The main end-to-end walkthrough: prepare data, generate hidden states, train, and serve. Covers Eagle-3, P-EAGLE, DFlash, DSpark, and MTP, in online, offline, or hybrid mode -- pick your algorithm and mode at the top of the page.

## [Multi-Node Training](multi_node_training.md)

Stream hidden states between separate extraction and training nodes with the Mooncake backend when the target model does not fit on one node or shared storage is unavailable.

## [Response Regeneration](response_regeneration.md)

Regenerate dataset responses using your target model for improved drafter alignment. Recommended before training.

## [Evaluating Model Performance](evaluating_performance.md)

Benchmark and evaluate your trained speculator models.

## [Serve in vLLM](serve_vllm.md)

Deploy your trained speculator models in vLLM for production inference.