Fine Tuning With Trl

You're looking at a wrapper for TRL (Transformer Reinforcement Learning), the library that handles post-training alignment for language models. It covers supervised fine-tuning, reward modeling, and RLHF workflows, giving you the standard toolkit for instruction tuning or aligning models with human preferences. The skill comes from orchestra-research's AI research collection and has passed most security audits, though Snyk flagged a warning. It's practical if you're doing any kind of model customization beyond base pretraining, but the skill itself is pretty minimal. You're mostly getting quick access to TRL's API through Claude Code rather than novel abstractions on top of it.

skills.sh installs: 1K
GitHub stars: 14.4K
last updated: Aug 21, 2026

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Install

$ npx -y skills add orchestra-research/ai-research-skills --skill fine-tuning-with-trl --agent claude-code

Installs into .claude/skills of the current project.

Files

TRL - Transformer Reinforcement Learning

Quick start

TRL provides post-training methods for aligning language models with human preferences.

Installation:

pip install trl transformers datasets peft accelerate

Supervised Fine-Tuning (instruction tuning):

from trl import SFTTrainer

trainer = SFTTrainer(
    model="Qwen/Qwen2.5-0.5B",
    train_dataset=dataset,  # Prompt-completion pairs
)
trainer.train()

DPO (align with preferences):

from trl import DPOTrainer, DPOConfig

config = DPOConfig(output_dir="model-dpo", beta=0.1)
trainer = DPOTrainer(
    model=model,
    args=config,
    train_dataset=preference_dataset,  # chosen/rejected pairs
    processing_class=tokenizer
)
trainer.train()

Common workflows

Workflow 1: Full RLHF pipeline (SFT → Reward Model → PPO)

Complete pipeline from base model to human-aligned model.

Copy this checklist:

RLHF Training:
- [ ] Step 1: Supervised fine-tuning (SFT)
- [ ] Step 2: Train reward model
- [ ] Step 3: PPO reinforcement learning
- [ ] Step 4: Evaluate aligned model

Step 1: Supervised fine-tuning

Train base model on instruction-following data:

SKILL.md on GitHub