| # PubMedBERT Abstract + Full Text Fine-Tuned on QNLI Task | |
| Use case: You can use it to search through a document for a given question, to see if your question is answered in that document. | |
| LABEL0 is "not entailment" meaning your question is not answered by the context and LABEL1 is "entailment" meaning your question is answered. | |
| > Example input: [CLS] Your question [SEP] The context to be searched in [SEP] | |
| Link to the original model: https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext | |
| Credits to the paper: | |
| > @misc{pubmedbert, author = {Yu Gu and Robert Tinn and Hao Cheng and | |
| > Michael Lucas and Naoto Usuyama and Xiaodong Liu and Tristan Naumann | |
| > and Jianfeng Gao and Hoifung Poon}, title = {Domain-Specific | |
| > Language Model Pretraining for Biomedical Natural Language | |
| > Processing}, year = {2020}, eprint = {arXiv:2007.15779}, } | |