openai/summarize-from-feedback resource

Health v2 · maintenance only

Flags: no_releases archived no_license

Adoption not part of the score

1062 stars · 153 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Research code and human feedback dataset from OpenAI's paper 'Learning to Summarize from human feedback', including a supervised baseline, a trained reward model, and an RL fine-tuned summarization policy. The repo is archived and provided as-is, with 64,832 summary comparisons on the TL;DR dataset plus evaluation data.

Use cases

• reproduce rlhf summarization experiments from the openai paper
• download human feedback comparison data for summarization research
• run a trained reward model to score text summaries
• generate summaries with a ppo fine-tuned policy on a gpu
• study reward model evaluation on tldr and cnn/dm datasets

When to choose

• you need the original human feedback dataset for rlhf research
• you want to reproduce or study the learning-to-summarize paper
• you need example code for reward models and ppo fine-tuning

When to avoid

• you need maintained, up-to-date code or library support
• you want production summarization rather than research artifacts
• you cannot run python 3.7 on ubuntu with an nvidia gpu

Facets

dataset · maturity abandoned

machine-learning deep-learning nlp llm-training rag machine-learning large-language-models artificial-intelligence python reinforcement-learning human-feedback rlhf summarization reward-model research-code tldr-dataset archived natural-language-processing linux gpu

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For agents

markdown · JSON · MCP: product_card(name="openai/summarize-from-feedback")