| import streamlit as st | |
| from transformers import AutoTokenizer, AutoModelForSequenceClassification, Trainer, TextClassificationPipeline | |
| model_name = "mrm8488/distilroberta-finetuned-financial-news-sentiment-analysis" | |
| model = AutoModelForSequenceClassification.from_pretrained(model_name) | |
| tokenizer = AutoTokenizer.from_pretrained(model_name) | |
| pipe = TextClassificationPipeline(model=model, tokenizer=tokenizer, return_all_scores=True) | |
| text = st.text_area(f'Ciao! This app uses {model_name}.\nEnter your text to test it ❤️') | |
| if text: | |
| out = pipe(text) | |
| st.json(out[0][0]) | |