fine-tuning-expert SKILL.md skillA
fine-tuning-expert from jeffallan/claude-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add jeffallan/claude-skills/fine-tuning-expert@v1.1.0Pins v1.1.0 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- jeffallan/claude-skills
- Path
skills/fine-tuning-expert/SKILL.md- Versions recorded
- 5
- Latest version
- v1.1.0, committed Oct 3, 2026
- First version recorded
- Mar 6, 2026
- Size
- 6,805 bytes
- Repository stars
- 12,006
- License
- MIT
Use when fine-tuning LLMs, training custom models, or adapting foundation models for specific tasks. Invoke for configuring LoRA/QLoRA adapters, preparing JSONL training datasets, setting hyperparameters for fine-tuning runs, adapter training, transfer learning, finetuning with Hugging Face PEFT, OpenAI fine-tuning, instruction tuning, RLHF, DPO, or quantizing and deploying fine-tuned models. Trigger terms include: LoRA, QLoRA, PEFT, finetuning, fine-tuning, adapter tuning, LLM training, model…
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# Fine-Tuning Expert Senior ML engineer specializing in LLM fine-tuning, parameter-efficient methods, and production model optimization. ## Core Workflow 1. **Dataset preparation** — Validate and format data; run quality checks before training starts - Checkpoint: `python validate_dataset.py --input data.jsonl` — fix all errors before proceeding 2. **Method selection** — Choose PEFT technique based on GPU memory and task requirements - Use LoRA for most tasks; QLoRA (4-bit) when GPU memory is constrained; full fine-tune only for small models 3. **Training** — Configure hyperparameters, monitor loss curves, checkpoint regularly - Checkpoint: validation loss must decrease; plateau or increase signals overfitting 4. **Evaluation** — Benchmark against the base model; test on held-out set and edge cases - Checkpoint: collect perplexity, task-specific metrics (BLEU/ROUGE), and latency numbers 5. **Deployment** — Merge adapter weights, quantize, measure inference throughput before serving ## Reference Guide Load detailed guidance based on context: | Topic | Reference | Load When | |-------|-----------|-----------| …
Read the whole file at its exact version.
How to install
mdr add jeffallan/claude-skills/fine-tuning-expert@sha256:87ad37743797487cThe line at the top of this page pins the label v1.1.0, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_6ttilobfayiegtsj)
2 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 5 versions of this file, between Mar 6, 2026 and Oct 3, 2026, about one every 53 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| v1.1.0 latest | 2026-10-03 | 958e60f | 6,805 B | A | view · diff |
| v1.1.0 | 2026-10-03 | ec755b7 | 6,723 B | A | view · diff |
| v1.1.0 | 2026-04-29 | efebc44 | 6,629 B | A | view · diff |
| v1.1.0 | 2026-03-06 | c7afefb | 6,534 B | A | view · diff |
| v1.0.0 | 2026-03-06 | cba3273 | 6,534 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (6805 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
jeffallan/claude-skills · 12,006 stars · license MIT · pushed 2026-10-21 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_6ttilobfayiegtsj GET https://markdownregistry.com/api/v1/resolve?ref=jeffallan/claude-skills/fine-tuning-expert GET https://markdownregistry.com/api/v1/blob/87ad37743797487cd1c37c23229357fc98fadf1e07a13c57b81e0c133e9cf4c3
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.
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