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Reinforcement Learning · Training · Safety

Zephyr

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First page
Zephyr
The curator’s take

Hugging Face's Zephyr-7B is a 7B parameter LLM whose chat performance rivals much larger chat models aligned with human feedback.

Key points
01

Distilled SFT: Uses distilled supervised fine-tuning on UltraChat-generated instruction data as the task-accuracy foundation.

02

Distilled DPO: Aligns with AI feedback data via Direct Preference Optimization, rather than the expensive human-feedback RLHF pipeline.

03

ChatGPT-level at 7B: Achieves competitive performance with ChatGPT on AlpacaEval and matches 70B chat models aligned with human feedback on several benchmarks.

04

Recipe popularization: Open-sources the distilled-DPO recipe, which became a widely adopted template for small, strong open chat models.

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