From 5aafe980fc1e2d4b9eecc6597e66cc5014c6b32b Mon Sep 17 00:00:00 2001 From: Jinhyuk Lee Date: Fri, 15 Mar 2019 15:26:39 +0900 Subject: [PATCH] Update README.md --- README.md | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/README.md b/README.md index fce0577..afa848e 100644 --- a/README.md +++ b/README.md @@ -3,10 +3,9 @@ This repository provides fine-tuning codes of BioBERT, a language representation ## Updates * **(3 Feb 2019)** Updated our [arxiv paper](http://arxiv.org/abs/1901.08746). -* **(31 Jan 2019)** Resolved [NER evaluation metric issue](https://github.com/dmis-lab/biobert/issues/3). ## Installation -To use BioBERT, we need pre-trained weights of BioBERT, which you can download from [Naver GitHub repository for BioBERT pre-trained weights](https://github.com/naver/biobert-pretrained). Note that this repository is based on the [BERT repository](https://github.com/google-research/bert) by Google. +To use BioBERT, we need pre-trained weights of BioBERT, which you can download from [Naver GitHub repository for BioBERT pre-trained weights](https://github.com/naver/biobert-pretrained). Make sure to specify the versions of pre-trained weights used in your works. Also, note that this repository is based on the [BERT repository](https://github.com/google-research/bert) by Google. All the fine-tuning experiments were conducted on a single TITAN Xp GPU machine which has 12GB of RAM. The code was tested with Python2 and Python3 (We used Python2 for experiments). You might want to install `java` to use official evaluation script of BioASQ. See `requirements.txt` for other details.