Search Results for author:
Found 1 papers, 0 papers with code
Small Language Models are Good Too: An Empirical Study of Zero-Shot Classification
This study is part of the debate on the efficiency of large versus small language models for text classification by prompting. We assess the performance of small language models in zero-shot text classification, challenging the prevailing dominance of large models. Across 15 datasets, our investigation benchmarks language models from 77M to 40B parameters using different architectures and scoring functions.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
