# Load model directly
import ast

from transformers import AutoTokenizer, AutoModelForSequenceClassification
import torch
# assets_path = cached_assets_path(library_name="datasets", namespace="SQuAD", subfolder="download")
# something_path = assets_path / "config.json" # Do anything you like in your assets folder !

tokenizer = AutoTokenizer.from_pretrained("pretrained_models/Bio_ClinicalBERT-finetuned-medicalcondition")
model = AutoModelForSequenceClassification.from_pretrained("pretrained_models/Bio_ClinicalBERT-finetuned-medicalcondition")
input=tokenizer("I love using transformers for natural language processing.", return_tensors="pt")

# 使用模型进行预测
with torch.no_grad():
    logits = model(**input).logits
# 解析预测结果
predicted_class_id = logits.argmax().item()
print(f"Predicted class id: {predicted_class_id}")