May 17, 2022, 2:30 p.m. | Synced

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In the new paper Standing on the Shoulders of Giant Frozen Language Models, AI21 Labs researchers propose three novel methods for learning small neural modules that specialize a frozen language model to different tasks. Their compute-saving approach outperforms conventional frozen model methods and challenges fine-tuning performance without sacrificing model versatility.


The post AI21 Labs’ Augmented Frozen Language Models Challenge Conventional Fine-Tuning Approaches Without Sacrificing Versatility first appeared on Synced.

ai ai21 labs artificial intelligence challenge deep-neural-networks fine-tuning labs language language model language models machine learning machine learning & data science ml research technology

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