fine-tuning-with-trl
fine-tuning-with-trl is a Fine-tuning & training data skill for AI agents, published by math-inc in the OpenGauss repository on GitHub. Skillspace rates fine-tuning-with-trl B (84/100) and it passed the safety scan; the rating is based on static analysis only.
Fine-tune LLMs using reinforcement learning with TRL - SFT for instruction tuning, DPO for preference alignment, PPO/GRPO for reward optimization, and reward model training. Use when need RLHF, align model with preferences, or train from human feedback. Works with HuggingFace Transformers.
- Grade
- B
- Quality
- 84 / 100
- Safety
- Passed
- GitHub stars
- 1,237
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
- 94 / 100
- Maturity
- Packaged: licensed, with a version or references
- Security scan
- No issues found
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 0 collections
- Scope
- Vendor-specific: built around one product. Documents HuggingFace's public TRL library
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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