Starling is a large language model trained by reinforcement learning from AI feedback focused on improving chatbot helpfulness.
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Updated 7 months ago
7 months ago
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Starling-7B is an open (non-commercial) large language model (LLM) trained by reinforcement learning from AI feedback. (RLAIF)
The model harnesses the power of our new GPT-4 labeled ranking dataset, Nectar, and our new reward training and policy tuning pipeline. Starling-7B-alpha scores 8.09 in MT Bench with GPT-4 as a judge, outperforming every model to date on MT-Bench except for OpenAI’s GPT-4 and GPT-4 Turbo.
*Based on MT Bench evaluations, using GPT-4 scoring. Further human evaluation is needed.
Authors: Banghua Zhu, Evan Frick, Tianhao Wu, Hanlin Zhu and Jiantao Jiao.
For correspondence, please contact Banghua Zhu (banghua@berkeley.edu).
Reference
Starling-7B: Increasing LLM Helpfulness & Harmlessness with RLAIF