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Michihiro Yasunaga

michiyasunaga

Language model, Multimodal model

Models in Library3
Datasets in Library0
Models on Hugging Face6
Followers14

Models

Model · Text classification

BioLinkBERT-large

Michihiro Yasunaga

BioLinkBERT-large model pretrained on PubMed abstracts along with citation link information. It is introduced in the paper LinkBERT: Pretraining Language Models with Document Links (ACL 2022). The code and data are available in this repository. This model achieves state-of-the-art performance on several biomedical NLP benchmarks such as BLURB and MedQA-USMLE. LinkBERT is a transformer encoder (BERT-like) model pretrained on a large corpus of documents. It is an improvement of BERT that newly captures document links such as hyperlinks and citation links to include knowledge that spans across multiple documents. Specifically, it was pretrained by feeding linked documents into the same…

Open weights apache-2.0 512 tokens transformers

Model · Text classification

BioLinkBERT-base

Michihiro Yasunaga

BioLinkBERT-base model pretrained on PubMed abstracts along with citation link information. It is introduced in the paper LinkBERT: Pretraining Language Models with Document Links (ACL 2022). The code and data are available in this repository. This model achieves state-of-the-art performance on several biomedical NLP benchmarks such as BLURB and MedQA-USMLE. LinkBERT is a transformer encoder (BERT-like) model pretrained on a large corpus of documents. It is an improvement of BERT that newly captures document links such as hyperlinks and citation links to include knowledge that spans across multiple documents. Specifically, it was pretrained by feeding linked documents into the same language…

Open weights apache-2.0 512 tokens transformers

Model · Text classification

LinkBERT-large

Michihiro Yasunaga

LinkBERT-large model pretrained on English Wikipedia articles along with hyperlink information. It is introduced in the paper LinkBERT: Pretraining Language Models with Document Links (ACL 2022). The code and data are available in this repository. LinkBERT is a transformer encoder (BERT-like) model pretrained on a large corpus of documents. It is an improvement of BERT that newly captures document links such as hyperlinks and citation links to include knowledge that spans across multiple documents. Specifically, it was pretrained by feeding linked documents into the same language model context, besides a single document. LinkBERT can be used as a drop-in replacement for BERT. It achieves…

Open weights apache-2.0 512 tokens transformers