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gebert_eng_graphsage
andorei/gebert_eng_graphsage
gebert_eng_graphsage is a feature extraction model from andorei. Use it when you need embeddings to search or compare text. It is set up for transformers.
The GEBERT model pre-trained with GAT graph encoder.
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At a glance
- Task
- Feature Extraction
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Sep 15, 2023
- Updated
- Oct 11, 2023
- SHA
- 6dad0386
Model card
From the Hugging Face model README
The GEBERT model pre-trained with GAT graph encoder.
The model was published at CLEF 2023 conference. The source code is available at github.
Pretraining data: biomedical concept graph and concept names from the UMLS (2020AB release).
Base model: microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext.
@inproceedings{sakhovskiy2023gebert,
author="Sakhovskiy, Andrey
and Semenova, Natalia
and Kadurin, Artur
and Tutubalina, Elena",
title="Graph-Enriched Biomedical Entity Representation Transformer",
booktitle="Experimental IR Meets Multilinguality, Multimodality, and Interaction",
year="2023",
publisher="Springer Nature Switzerland",
address="Cham",
pages="109--120",
isbn="978-3-031-42448-9"
}
- Task
- Feature Extraction
- Library
- transformers
- Type
- bert
- Languages
- en
- Created
- Sep 15, 2023
- Updated
- Oct 11, 2023