---
name: model-trainer
description: >
  Weekly fine-tuning of local LLM models using accumulated Wall-E data.
  Exports training data, runs fine-tuning on supported base models,
  evaluates results against a baseline, and deploys the winner.
version: 1.0.0
author: wall-e
execution: script
entry: index.js
trigger:
  type: interval
  interval_seconds: 604800
tags: [training, fine-tuning, llm, ollama, model]
permissions:
  - brain:read
config:
  enabled: false
---
# Model Trainer

Runs the full fine-tuning pipeline on a weekly schedule (disabled by default).

## Pipeline

1. **Export** training data from brain (knowledge, chat, patterns)
2. **Train** all supported base models (llama3.1-8b, phi-4, qwen2.5-7b, gemma4-4b)
3. **Evaluate** trained models against a baseline using benchmark prompts
4. **Deploy** the winner to Ollama if it beats the baseline by >60%

## Enabling

Set `config.enabled: true` in this skill's metadata or enable via the API.
Requires at least 100 training samples in the brain before training will proceed.
