Fine-tuning & training data

The top-rated launch-quality Fine-tuning & training data skill for AI agents is peft-fine-tuning (grade B), followed by nemo-curator and slime-rl-training. Skillspace rates 219 Fine-tuning & training data skills; 60 are launch-quality.

Fine-tuning, LoRA, dataset curation, synthetic data and preference data.

Launch-quality skills first, then by grade, then by our Skill Score, which adds judge reviews, test results, GitHub stars and adoption.

  1. peft-fine-tuning B
  2. nemo-curator B
  3. slime-rl-training B
  4. fine-tuning-with-trl B
  5. agents-meet-rl B
  6. unsloth B
  7. finetuning-technique B
  8. Training B
  9. incinerate B
  10. axolotl B
  11. i4h-workflow-dataset-mimic B
  12. i4h-workflow-dataset-transfer B
  13. dspy-finetune-bootstrap B
  14. nemo-data-designer-plugin B
  15. dataset-search-tools B
  16. sop-data-augmentation B
  17. book-sft-pipeline B
  18. secondme-skill B
  19. safe-synthesizer B
  20. black-dataops B
  21. persona-knowledge B
  22. autonomous-llm-research B
  23. synthetic-data-generation B
  24. fine-tuning-data-generator B
  25. vision-sft C

Frequently asked questions

What is the best Fine-tuning & training data skill for AI agents?

The top-rated launch-quality Fine-tuning & training data skill for AI agents is peft-fine-tuning (grade B), followed by nemo-curator and slime-rl-training. Skillspace rates 219 Fine-tuning & training data skills; 60 are launch-quality.

How does Skillspace rate Fine-tuning & training data skills?

Skillspace grades every Fine-tuning & training data skill from A to F with a published scoring engine that reads the skill's SKILL.md: architecture and maturity make the score, and a security scan can cap it. In crowded categories, a judge model also compares the strongest contenders side by side, and some skills are tested head-to-head on real tasks against other skills in the same category (including a deliberately weak one) and a no-skill baseline. Launch-quality skills are graded A to C with a clean safety verdict, and not excluded by a quality filter: the filters catch skills our model's safety screen flags for prompt injection, guardrail bypass, harmful content or credential exposure; test fixtures and attack benchmarks; skills written only for the repository they live in; templates and stubs; and near-duplicate variants and copies of other skills. Ratings were last updated on 24 September 2026; the full method is on the methodology page.

Are Fine-tuning & training data skills safe to install?

Of the 219 Fine-tuning & training data skills Skillspace rates, 186 passed its safety scan and 33 are flagged: 1 for review, 27 as risky and 5 as unsafe. Each skill's page shows its safety verdict. A pass is not a guarantee: the scan reads only the skill's SKILL.md, not the scripts or other files it ships, and looks for patterns such as piping a remote script into a shell, reading credentials or hiding actions from the user. Skills are third-party code that Skillspace indexes but does not host or endorse, so read a skill's source on GitHub before you install it.

Skillspace indexes and rates skills; it does not host or endorse them. Run third-party skills at your own risk.