Python Bridge Embeddings

Deploy on-premise python models BERT, MiniLM, T5, GTR-T5 for vector embedding generation of the content extracted from the documents. It can handle one text per document or an array of text segments to get the embeddings for them.

Prerequisites

About the Python Bridge Embeddings application for Aspire, how it works, and features.

How to Configure

This is a step-by-step tutorial to configure the Python Bridge Embeddings application.

Troubleshooting

These are common questions and answers, as well as troubleshooting techniques for the Python Bridge Embeddings application.