transformers pytorch xlm-roberta token-classification medical fill-mask multilingual en zh arxiv:2311.11564 license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
language:
- multilingual
- en
- zh
license: apache-2.0
pipeline_tag: fill-mask
tags:
- medical
---

# KBioXLM

The aligned corpus constructed using the knowledge-anchored method is combined with a multi task training strategy to continue training XLM-R, thus obtaining KBioXLM. It is the first multilingual biomedical pre-trained language model we know that has cross-lingual understanding capabilities in medical domain. It was introduced in the paper [KBioXLM: A Knowledge-anchored Biomedical
Multilingual Pretrained Language Model](http://arxiv.org/abs/2311.11564) and released in [this repository](https://github.com/ngwlh-gl/KBioXLM/tree/main).

## Model description
KBioXLM model can be fintuned on downstream tasks. The downstream tasks here refer to biomedical cross-lingual understanding tasks, such as biomedical entity recognition, biomedical relationship extraction and biomedical text classification.

## Usage

You can follow the prompts below to load our model parameters:

```python
from transformers import RobertaModel
model=RobertaModel.from_pretrained('ngwlh/KBioXLM')
```

### BibTeX entry and citation info

Coming soon.