Anthropic HH Golden RLHF: Human Preference Data for Language Model Alignment

A dataset from Anthropic, published on HuggingFace by user 'nz' and last updated on February 2, 2024. The title suggests it contains data for Reinforcement Learning from Human Feedback (RLHF), a technique for aligning language models. The specific content, scale, and structure require verification after download.

Use Cases

• Training a reward model to predict human preferences (inferred from domain, verify after download)
• Fine-tuning a language model using Proximal Policy Optimization (PPO) with human feedback (inferred from domain, verify after download)
• Benchmarking alignment techniques on a curated set of human preference comparisons (inferred from domain, verify after download)

Strengths

• Published on the HuggingFace platform, a major hub for AI datasets.
• Last update timestamp (2024-02-02 16:15:18) is provided.

Limitations

• Metadata is minimal; actual content requires verification after download.
• Row count, column definitions, and sample data are unavailable, limiting suitability assessment.
• License information is unknown, which may restrict usage.

Provenance

Source

Anthropic (inferred from title), uploaded by user 'nz' to HuggingFace.

Freshness

Last updated 2024-02-02 16:15:18.