Gen-Selective Pseudo Labeling, Based on Datasets and Serverless Inference API (github.com)

The Gen-Selective Pseudo Labeler (GSPL) is a tool designed to generate multiple queries about the same document and apply selection techniques using transformers. It leverages large language models (LLMs) to function as a judge, enhancing the labeling process through advanced completion and selection methods. This project is particularly useful in scenarios where multi-query generation and selection are required to improve the quality and relevance of labeled data.

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