import streamlit as st
from transformers import pipeline

from transformers import AutoTokenizer, BertForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("AkshatSurolia/ICD-10-Code-Prediction")
model = BertForSequenceClassification.from_pretrained("AkshatSurolia/ICD-10-Code-Prediction")
config = model.config



pipe = pipeline('sentiment-analysis')
text = st.text_area('test')


text = "subarachnoid hemorrhage scalp laceration service: surgery major surgical or invasive"
encoded_input = tokenizer(text, return_tensors='pt')
output = model(**encoded_input)

results = output.logits.detach().cpu().numpy()[0].argsort()[::-1][:5]
return [ config.id2label[ids] for ids in results]