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Status: Unchecked ×Keyword: QLoRA ×Clear all

1 claim from 1 paper

1. Computer Science › Natural Language Processing Techniques

   Machine Translation with Large Language Models: Prompting, Few-shot Learning, and Fine-tuning with QLoRA

   Zhang, Rajabi, Duh and Koehn · Conference on Machine Translation (WMT) · 2023

   The paper tests 15 public language models on machine translation using zero-shot prompting, few-shot learning and QLoRA fine-tuning, and reports that QLoRA does best on French-English.

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   1. UncheckedWith QLoRA, the improved French-English translation results come from fine-tuning only 0.77% of the language model's parameters.“Impressively, with QLoRA, the enhanced performance is achieved by finetuning a mere 0.77% of the model's parameters.”