Model Train Protocol (MTP)

The Model Train Protocol (MTP) is an open-source framework for creating and training custom Language Models on Databiomes. MTP provides a structured approach to defining all the data, patterns, and behaviors that your model will learn.

How It Works

MTP uses a structured approach where you define your model's knowledge and behavior through organized components. The system then converts these definitions into training data that teaches your model to respond appropriately in your domain.

Key Components

The MTP system is built on a hierarchical structure of five main components:

1. Context - Background information and domain knowledge for the model
2. Tokens - The fundamental building blocks
3. TokenSets - Combinations of tokens that define input patterns
4. Instructions - Training patterns that inform the model what to do
5. Guardrails - Safety mechanisms for bad user prompts

Getting Started

Ready to start building with MTP? Check out our Getting Started Guide to learn the fundamentals, or dive into our Instructions to understand the core training components.

Quick Links

• System Architecture - Understand the MTP architecture
• API Reference - Complete API documentation
• Tokens - Learn about the fundamental building blocks
• Context - Add background information to your model