What does the Mei skill do?

Fine-tune with discipline: earn it, curate data, QLoRA/DPO, and prove it beats the base model on eval. Load it once into Claude Projects and you get a configured LLM Fine-tuning Engineer without re-explaining context at the start of every session. Build and evaluate against a held-out test set in a development or staging environment, add guardrails, cost and rate limits, and human review, and roll out behind evals and monitoring before serving agents or LLM features in production.

How do I install this skill file?

Download the .skill package (it contains SKILL.md), paste the contents into Claude Projects Instructions or your AI's system prompt, add your own context and start your first session. Works with Claude, ChatGPT, or any AI chat that accepts system prompts.

Which AI tools does this skill work with?

Works with Claude (recommended), ChatGPT, Gemini, Perplexity and Copilot, and any AI chat that accepts system prompts. Claude Projects gives the best results.

What is included in this download?

One .skill package delivered instantly after purchase: the full SKILL.md role configuration plus a worked-example file with a real scenario so you see the quality before you rely on it. No subscription, yours permanently.

How is this different from using Claude without the Mei skill?

Without a skill file your AI starts every session as a general assistant. With Mei loaded it applies LLM Fine-tuning Engineer methodology from the first message, with consistent quality every time. Build and evaluate against a held-out test set in a development or staging environment, add guardrails, cost and rate limits, and human review, and roll out behind evals and monitoring before serving agents or LLM features in production.

LLM Fine-tuning Engineer AI Skill for Claude & ChatGPT

Name: Mei — LLM Fine-tuning Engineer AI Skill
Brand: KissMySkills
Price: 34.0 USD
Availability: InStock

Mei — LLM Fine-tuning Engineer AI Skill

$34.00

Mei — LLM Fine-tuning Engineer AI Skill

$34.00

⚡ Instant download ◆ Claude & ChatGPT ∞ Keep forever

Instant download · 30-day money-back guarantee. Pay once, keep forever — no subscription. Refund policy

Fine-tune with discipline: earn it, curate data, QLoRA/DPO, and prove it beats the base model on eval.

When NOT to fine-tune vs when it genuinely wins
Dataset curation: dedup, decontamination, chat templating
QLoRA/LoRA and preference tuning (DPO/ORPO/KTO) with defaults
GPU-memory math, forgetting checks and base-vs-tuned eval

Teams reaching for a fine-tune, who want it to actually pay off and not regress the base model.A senior fine-tuning engineer bills $140+/hr, this is one file, yours forever.

// what's inside

Drop Mei into Claude and get a senior fine-tuning engineer whose first question is: have you exhausted prompting and RAG? You earn the fine-tune and prove it with eval.

Mei adapts LLMs the disciplined way: when not to fine-tune (prompt/RAG first) and when it genuinely wins (format and schema adherence, tool-call reliability, latency and cost via smaller models, domain tone), dataset curation (quality over quantity, dedup, decontamination against the eval set, chat templating), methods (full SFT vs PEFT: LoRA/QLoRA rank/alpha/target modules, learning rate, epochs, packing), preference tuning (DPO/ORPO/KTO), GPU-memory math, overfitting and catastrophic forgetting detection, evaluation vs the base model, and serving the adapter. Tools like Hugging Face TRL/PEFT, Axolotl, Unsloth and bitsandbytes, without lock-in. Always evaluate on a held-out set before serving.

What you get

→When NOT to fine-tune vs when it genuinely wins
→Dataset curation: dedup, decontamination, chat templating
→QLoRA/LoRA and preference tuning (DPO/ORPO/KTO) with defaults
→GPU-memory math, forgetting checks and base-vs-tuned eval

📄 mei-llm-finetuning-engineer.skill Under 2 min install Works with Claude, ChatGPT & any AI chat

How to install

Download the .skill package → open Claude → paste SKILL.md into your Project Instructions or system prompt → describe your requirement → Mei builds the answer. Includes a full worked example so you see exactly what you get.

mei-llm-finetuning-engineer.skill

# Mei - LLM Fine-tuning Engineer

You are Mei, a senior LLM Fine-tuning Engineer. You earn the fine-tune and prove it with eval.

## How you work
1. Ask: have you exhausted prompting and RAG?
2. Curate the dataset (dedup, decontaminate, template)
3. Train (QLoRA/LoRA or DPO) with sane defaults and VRAM math
4. Evaluate vs the base model; check for forgetting; then serve

Always evaluate on a held-out set in dev/staging before serving in production.

Excerpt from the actual file you'll download.

// try it

prompt

$We want reliable JSON tool-calls from a smaller model. Should we fine-tune, and if so, how?

Mei returns the fine-tune/don't decision, a dataset schema with a cleaning and decontamination script, a runnable TRL + PEFT QLoRA config, the VRAM math, and a base-vs-tuned eval table with a catastrophic-forgetting regression check.

// how to install Under 2 minutes

Four steps. Any AI chat.

01
Download the file
After checkout, the download link lands in your inbox. Save the file anywhere on your device.
02
Open your AI chat
Claude, ChatGPT, Gemini, Grok, or Copilot — whichever one you already use.
03
Paste the file contents
Drop it into the system prompt, Project instructions, or custom instructions field.
04
Start working
Your AI is now configured as a specialist. Ask it anything inside its domain.