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Hypencoder.2 Layer

Developed by jfkback
Hypencoder is a hypernetwork model for information retrieval, consisting of a text encoder and Hypencoder. It can convert text into a small neural network and output relevance scores.
Downloads 18
Release Time : 2/12/2025

Model Overview

This model is mainly used for information retrieval tasks, evaluating relevance by converting text into neural networks.

Model Features

Dual encoder structure
It contains a text encoder and Hypencoder, which process text and generate small neural networks respectively.
Configurable number of layers
It offers different variants with 2, 4, 6, and 8 layers, which can be selected according to requirements.
Hypernetwork technology
It uses hypernetwork technology to convert text into neural networks for relevance evaluation.

Model Capabilities

Text feature extraction
Relevance scoring
Information retrieval

Use Cases

Information retrieval
Question - answering system
Used to evaluate the relevance between questions and answer paragraphs.
Can output relevance scores
Document retrieval
Retrieve the documents most relevant to the query.
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