How to use from the
Use from the
Transformers library
# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("fill-mask", model="ngwlh/KBioXLM")
# Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification

tokenizer = AutoTokenizer.from_pretrained("ngwlh/KBioXLM")
model = AutoModelForTokenClassification.from_pretrained("ngwlh/KBioXLM")
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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 and released in this repository.

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:

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

BibTeX entry and citation info

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Paper for ngwlh/KBioXLM