custom-models

Guide to implementing custom model architectures in LitGPT.

Skills
AI research
4

What it does and how to use it

A skill that teaches Claude Code to do ai research tasks well. It is packaged knowledge the model uses whenever it is relevant.

Install the skill (command above).
In Claude Code, describe what you need - the skill turns on by itself when the context fits.
No commands to memorize: you talk in plain language and the skill does the rest.

Install (Claude Code)

mkdir -p .claude/skills/custom-models && curl -fsSL https://doutorai.pt/data/lib/skills__custom-models.md -o .claude/skills/custom-models/SKILL.md

Paste this command into the terminal, in your project folder, and the component installs automatically.

Content

# Custom Models

Guide to implementing custom model architectures in LitGPT.

## Overview

LitGPT's clean, single-file implementations make it easy to create custom architectures. You can extend the base `GPT` class or create entirely new models.

**Use cases**:
- Implementing new research architectures
- Adapting models for specific domains
- Experimenting with attention mechanisms
- Adding custom layers or components

## Key Files and Classes

### Core Architecture (`litgpt/model.py`)

**Main classes**:
- `GPT`: Top-level model class
- `Block`: Transformer block (attention + MLP)
- `CausalSe

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