fine-tuning-expert
fine-tuning-expert is a Fine-tuning & training data skill for AI agents, published by Jeffallan in the claude-skills repository on GitHub. Skillspace rates fine-tuning-expert C (77/100) and it passed the safety scan; a judge model has also reviewed it.
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 training, custom model.
- Grade
- C
- Quality
- 77 / 100
- Safety
- Passed
- GitHub stars
- 10,602
Placed #3 of 6 in the judged category final for Fine-tuning & training data.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 100 / 100
- Maturity
- Packaged: licensed, with a version or references
- Security scan
- Low-risk patterns
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 0 collections
- Scope
- Portable: works in any project. General LLM fine-tuning methodology spanning many tools and providers
Judge review
Placed #3 of 6 in the judged category final for Fine-tuning & training data.
- Trigger
90 90 - Instructions
92 92 - Specificity
93 93 - Safety
85 85 - Disclosure
85 85 - Maintenance
55 55
A complete, runnable LoRA/QLoRA walkthrough with checkpoint gates between steps and explicit must/must-not rules covering the common failure modes.
What the scanner flagged
- mentions secrets in text
Not checked yet
- No blind task eval yet
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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