6 skills from other authors that do a similar job to fine-tuning-expert by Jeffallan. The most recently updated is peft-fine-tuning (Jun 16, 2026).
| Skill | Stars | License | Agents | Last update | Category | Install |
|---|---|---|---|---|---|---|
| fine-tuning-expert by Jeffallan · this skill | 11,060 | MIT | Claude Code | Aug 7, 2026 | Data | Plugin marketplace |
| peft-fine-tuning by Orchestra-Research | 11,807 | MIT | Claude Code, Codex | Jun 16, 2026 | Workflow | Plugin marketplace |
| fine-tuning-with-trl by Orchestra-Research | 11,807 | MIT | Claude Code, Codex | Jun 16, 2026 | Productivity | Plugin marketplace |
| axolotl by Orchestra-Research | 11,807 | MIT | Claude Code, Codex | Jun 16, 2026 | Data | Plugin marketplace |
| grpo-rl-training by Orchestra-Research | 11,807 | MIT | Claude Code, Codex | Jun 16, 2026 | Productivity | Plugin marketplace |
| llama-factory by Orchestra-Research | 11,807 | MIT | Claude Code, Codex | Jun 16, 2026 | Frontend | Plugin marketplace |
| unsloth by Orchestra-Research | 11,807 | MIT | Claude Code, Codex | Jun 16, 2026 | Workflow | Plugin marketplace |
Alternatives are matched on overlapping names, descriptions, tags and SKILL.md sections, weighted by how rare each term is across the catalog. Data refreshed weekly from GitHub.
Parameter-efficient fine-tuning for LLMs using LoRA, QLoRA, and 25+ methods. Use when fine-tuning large models (7B-70B) with limited GPU memory, when you need to train <1% of parameters with minimal accuracy loss, or for multi-adapter serving. HuggingFace's official library integrated with transformers ecosystem.
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.
Expert guidance for fine-tuning LLMs with Axolotl - YAML configs, 100+ models, LoRA/QLoRA, DPO/KTO/ORPO/GRPO, multimodal support
Expert guidance for GRPO/RL fine-tuning with TRL for reasoning and task-specific model training
Expert guidance for fine-tuning LLMs with LLaMA-Factory - WebUI no-code, 100+ models, 2/3/4/5/6/8-bit QLoRA, multimodal support
Expert guidance for fast fine-tuning with Unsloth - 2-5x faster training, 50-80% less memory, LoRA/QLoRA optimization
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