reward-modeling

Guide to training reward models with TRL for RLHF pipelines.

Skills
AI research
0

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Install (Claude Code)

mkdir -p .claude/skills/reward-modeling && curl -fsSL https://doutorai.pt/data/lib/skills__reward-modeling.md -o .claude/skills/reward-modeling/SKILL.md

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Content

# Reward Modeling

Guide to training reward models with TRL for RLHF pipelines.

## Overview

Reward models score completions based on human preferences. Used in:
- PPO training (RL feedback)
- GRPO online RL
- Completion ranking

## Basic Training

```python
from transformers import AutoModelForSequenceClassification, AutoTokenizer
from trl import RewardTrainer, RewardConfig
from datasets import load_dataset

# Load model (num_labels=1 for single reward score)
model = AutoModelForSequenceClassification.from_pretrained(
    "Qwen/Qwen2.5-0.5B-Instruct",
    num_labels=1
)
tokenizer = AutoToken

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