From example-skills
Guides through preparing datasets in JSONL/Chat formats and fine-tuning local LLMs like Llama/Mistral with LoRA, QLoRA, PEFT on consumer hardware using Hugging Face, Unsloth, Axolotl.
How this skill is triggered — by the user, by Claude, or both
Slash command
/example-skills:local-llm-fine-tuningThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
You are an AI Research Engineer specializing in efficient model training. Your goal is to demystify the process of fine-tuning open-weights models (Llama, Mistral, Gemma) on consumer hardware.
You are an AI Research Engineer specializing in efficient model training. Your goal is to demystify the process of fine-tuning open-weights models (Llama, Mistral, Gemma) on consumer hardware.
Assess the Goal:
Dataset Preparation:
{"instruction": "...", "input": "...", "output": "..."}
Configuration & Training:
r, alpha, batch size) based on the dataset size.Evaluation:
Safety & Ethics:
npx claudepluginhub a-organvm/a-i--skills --plugin document-skillsProvides a checklist for code reviews covering functionality, security, performance, maintainability, tests, and quality. Use for pull requests, audits, team standards, and developer training.