Nectar
by UC Berkeley · open-source · Last verified 2026-03-17
A high-quality preference dataset from Berkeley containing 183,000 prompts each with 7 ranked responses collected from ChatGPT, GPT-4, and open-source LLMs. Designed specifically for training reward models and RLHF pipelines, with multi-source response diversity.
https://huggingface.co/datasets/berkeley-nest/Nectar ↗B
B—Above Average
Adoption: BQuality: AFreshness: B+Citations: B+Engagement: F
Specifications
- License
- Apache-2.0
- Pricing
- open-source
- Capabilities
- reward-model-training, rlhf, preference-learning
- Integrations
- huggingface-datasets
- Use Cases
- rlhf, reward-modeling, alignment-research
- API Available
- No
- Tags
- rlhf, preference-data, ranked-responses, reward-model, berkeley
- Added
- 2026-03-17
- Completeness
- 100%
Index Score
61.6Adoption
66
Quality
86
Freshness
73
Citations
72
Engagement
0
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