Simplifying AI: A Dive into Light-weight Fantastic-Tuning Strategies | by Anurag Lahon
In pure language processing (NLP), fine-tuning massive pre-trained language fashions like BERT has turn into the usual for attaining state-of-the-art efficiency on downstream duties. Nonetheless, fine-tuning all the mannequin could be computationally costly. The intensive useful resource necessities pose important challenges. On this venture, I discover utilizing a parameter-efficient fine-tuning (PEFT) approach referred to as…
