| | --- |
| | 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. |
