LLM Fine-tuning Engineer AI Skill - Mei
Fine-tune with discipline: earn it, curate data, QLoRA/DPO, and prove it beats the base model on eval.
Claude skill package instant downloadmei-llm-finetuning-engineer.skill
Get this skill and 2,500+ others
$9/mo or $59 a year
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One file, paid once. No updates, no connector.
Costs about the same as 2 months of Library.
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How it works
Ask it something hard.
Or have every skill inside your AI.
Questions before you buy? A person answers, usually the same day: hello@kissmyskills.com
// the file itself
The first lines of the file your AI will read, exactly as delivered. Nothing rewritten for the page.
You are Mei, a Senior LLM Fine-tuning Engineer who builds the held-out eval first, then picks between LoRA, QLoRA and DPO in Hugging Face TRL or Axolotl. You have been activated to earn the fine-tune before the GPU bill.
// what's inside
Teams reaching for a fine-tune, who want it to actually pay off and not regress the base model.
// two ways to get it
$9/mo cancel anytime, or $59 a year
$19 one payment
Already on Library or Both? This one is included, no need to buy the file.
// ask your assistant
Go to kissmyskills.com/pages/connector and set up the "LLM Fine-tuning Engineer AI Skill - Mei" skill (handle: mei-llm-finetuning-engineer) for me
Paste it into Claude, ChatGPT, Claude Code, Cursor or Codex. Your AI walks you through connecting KissMySkills (about 3 minutes, 7-day free trial) and loads the skill. What your AI will read →
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
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.
After checkout, the download link lands in your inbox. Save the .skill file: Claude takes it as it is.
Any AI chat you already use: Claude, ChatGPT, Gemini, Grok, Copilot or another.
Claude: Settings → Capabilities → Skills, upload the .skill file. ChatGPT, Gemini and others: open the .skill file like a .zip archive and paste SKILL.md into custom instructions or Project instructions.
Your AI is now configured as a specialist. Ask it anything inside its domain.
No technical knowledge required.
With Library there is nothing to download. Connect your AI once, then just ask: "Load LLM Fine-tuning Engineer AI Skill from KissMySkills."
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.
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.
Works with Claude (recommended), ChatGPT, Gemini, Perplexity and Copilot, and any AI chat that accepts system prompts. Claude Projects gives the best results.
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.
This one and 2,500+ others, inside Claude, ChatGPT, Claude Code, Codex or Cursor. Cancel anytime.