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BOND-reranker

AronowLab

A cross-encoder reranker model fine-tuned for biomedical ontology entity normalization, designed to work with the BOND (Biomedical Ontology Neural Disambiguation) system. This model is a cross-encoder reranker trained to improve the accuracy of entity normalization by re-ranking candidate ontology terms retrieved by BOND's initial retrieval stage. It takes a query-candidate pair and outputs a relevance score. The model was trained on biomedical entity normalization data covering multiple ontologies including:

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EmoRoBERTa

arpanghoshal

基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

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Text analysis
Input Text→ Output Text
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Visual QA
Input Text · Image→ Output Text
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lzlv_70b-GGUF

Artefact2

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Yi-34B-GGUF

Artefact2

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TestMixtral

artek0chumak

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Text generation
Input Text→ Output Text
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