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Training · Evaluation · Data

Platypus

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Platypus
The curator’s take

Platypus is a family of fine-tuned and merged LLMs that topped the Open LLM Leaderboard in August 2023.

Key points
01

LoRA fine-tuning + merging: Describes an efficient process for fine-tuning and merging LoRA modules, demonstrating that careful composition beats monolithic fine-tuning.

02

Open-Platypus dataset: Releases a small, highly curated fine-tuning dataset that delivers strong performance with short and cheap training - quality over quantity.

03

5 hours on one A100: A 13B Platypus can be trained on a single A100 GPU using 25K curated questions in roughly 5 hours.

04

Leaderboard-topping: Demonstrates that careful data curation and LoRA merging can produce leaderboard-topping open models without massive compute.

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