diff --git a/README.md b/README.md index 9654d2c..073c36e 100644 --- a/README.md +++ b/README.md @@ -14,6 +14,7 @@ We provide five versions of pre-trained weights. Pre-training was based on the [ ## Installation Sections below describe the installation and the fine-tuning process of BioBERT based on Tensorflow 1 (python version <= 3.7). +For PyTorch version of BioBERT, you can check out [this repository](https://github.com/dmis-lab/biobert-pytorch). If you are not familiar with coding and just want to recognize biomedical entities in your text using BioBERT, please use [this tool](https://bern.korea.ac.kr) which uses BioBERT for multi-type NER and normalization. To fine-tune BioBERT, you need to download the [pre-trained weights of BioBERT](https://github.com/naver/biobert-pretrained). @@ -29,13 +30,14 @@ You might want to install `java` to use the official evaluation script of BioASQ ## Quick Links Link | Detail ------------- | ------------- +[BioBERT-PyTorch](https://github.com/dmis-lab/biobert-pytorch) | PyTorch-based BioBERT implementation [BERN](https://bern.korea.ac.kr) | Web-based biomedical NER + normalization using BioBERT [covidAsk](https://covidask.korea.ac.kr) | BioBERT based real-time question answering model for COVID-19 [7th BioASQ](https://github.com/dmis-lab/bioasq-biobert) | Code for the seventh BioASQ challenge winning model (factoid/yesno/list) [Paper](https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btz682/5566506) | Paper link with [BibTeX](https://github.com/dmis-lab/biobert#citation) (Bioinformatics) ## FAQs -* [How can I use BioBERT with PyTorch?](https://github.com/dmis-lab/biobert/issues/2) +* [How can I use BioBERT with PyTorch?](https://github.com/dmis-lab/biobert-pytorch) * [Can I get word/sentence embeddings using BioBERT?](https://github.com/dmis-lab/biobert/issues/23) * [How can I pre-train QA models on SQuAD?](https://github.com/dmis-lab/biobert/issues/10) * [What vocabulary does BioBERT use?](https://github.com/naver/biobert-pretrained/issues/1)