fine-tuning-llms
fine-tuning-llms is a Fine-tuning & training data skill for AI agents, published by pvillega in the claude-templates repository on GitHub. Skillspace rates fine-tuning-llms D (55/100) and it passed the safety scan; the rating is based on static analysis only.
Deep LLM fine-tuning operational intuition — LoRA/QLoRA merge pitfalls, preference optimization (DPO/ORPO/SimPO/GRPO), chat-template footguns, completion-only loss masking, sequence packing, eval contamination, toolchain (TRL/axolotl/unsloth/torchtune). Load when post-training open-weights models, picking preference-optimization methods, configuring LoRA/QLoRA, suspecting eval contamination, or choosing a toolchain. Skip for inference/serving (use `llm-inference-serving`), prompt engineering, RAG, or pretraining. Triggers on: "QLoRA", "merge_and_unload", "DPO", "ORPO", "SimPO", "GRPO", "GRPOTrainer", "axolotl", "unsloth", "torchtune", "nf4", "apply_chat_template", "DataCollatorForCompletionOnlyLM", "cu_seqlens", "MMLU contamination", "catastrophic forgetting".
- Grade
- D
- Quality
- 55 / 100
- Safety
- Passed
- GitHub stars
- 23
Unproven: rated by static analysis only, not yet compared head-to-head.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 84 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- Low-risk patterns
- License
- Not declared. Check the repository before reusing it.
- Adoption
- Adopted by 0 other repositories, in 0 collections
What the scanner flagged
- mentions secrets in text
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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