Does this require a high-end enterprise GPU?

No, the skill focuses on efficient techniques like QLoRA and tools like Unsloth that are specifically designed to enable fine-tuning on consumer-grade hardware with limited VRAM.

What models can I fine-tune using this skill?

This skill is designed for popular open-weights models including the Llama series, Mistral, and Google's Gemma models.

What is the benefit of using Unsloth or Axolotl via this skill?

The skill recommends Unsloth for the fastest training speeds on single GPUs and Axolotl for configuration-based, reproducible training runs.

How does this skill help with model evaluation?

It suggests automated benchmarks and specific evaluation prompts to help you verify if the model has successfully learned the new tasks without losing its base capabilities.

Which data formats are supported for training?

The skill provides guidance and conversion logic for standard instruction-tuning formats, primarily JSONL, using templates like Alpaca and ShareGPT.

Local LLM Fine-Tuning Specialist

Name: Local LLM Fine-Tuning Specialist
Author: organvm-iv-taxis

byorganvm-iv-taxis

•

数据科学与机器学习

Guides the preparation of datasets and the implementation of efficient fine-tuning techniques like LoRA and QLoRA for local large language models.

This skill transforms Claude into an AI Research Engineer specialized in the optimization of open-weights models such as Llama, Mistral, and Gemma on consumer-grade hardware. It provides comprehensive end-to-end guidance, ranging from the selection of the ideal base model and the conversion of raw data into instruction-tuned JSONL formats to the configuration of advanced hyperparameters for tools like Unsloth and Axolotl. By focusing on Parameter-Efficient Fine-Tuning (PEFT) methods, it enables users to customize AI behavior and knowledge bases while effectively managing VRAM constraints and avoiding common pitfalls like catastrophic forgetting.

主要功能

01Hardware-aware hyperparameter recommendations for VRAM optimization

02Troubleshooting for overfitting, EOS token issues, and model evaluation

03Dataset formatting scripts for JSONL, Alpaca, and ShareGPT templates

042 GitHub stars

05Expert guidance on LoRA, QLoRA, and PEFT implementation

06Support for popular frameworks including Hugging Face, Unsloth, and Axolotl

使用场景

01Adapting an open-weights model to a specific brand voice or specialized domain vocabulary

02Optimizing small-parameter models to consistently output specific data formats like JSON or SQL

03Training a local model on private technical documentation to act as an internal expert

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add organvm-iv-taxis/a-i--skills local-llm-fine-tuning

For use in Claude.ai and ChatGPT

Download Skill