yseop/SMM4H2024_Task2b_ja
09
SMM4H-2024 Task 2 Japanese RE
Overview
This is a relation extraction model created by fine-tuning daisaku-s/medtxt_ner_roberta on SMM4H 2024 Task 2b corpus.
Tag set:
- CAUSED
- TREATMENT_FOR
Usage
from transformers import AutoModelForSequenceClassification, AutoTokenizer
import torch
text = "サンプルテキスト"
model_name = "yseop/SMM4H2024_Task2b_ja"
id2label = ['O', 'CAUSED', 'TREATMENT_FOR']
with torch.inference_mode():
model = AutoModelForSequenceClassification.from_pretrained(model_name).eval()
tokenizer = AutoTokenizer.from_pretrained(model_name)
encoded_input = tokenizer(text, return_tensors='pt', max_length=512)
output = re_model(**encoded_input).logits
class_id = output.argmax().item()
print(id2label[class_id])