app.py

from typing import Any

from transformers import pipeline, LongformerForSequenceClassification, LongformerTokenizer, Trainer
import gradio as gr


def predict_fn(text: str) -> dict[str, Any]:
    model = LongformerForSequenceClassification.from_pretrained("model")
    tokenizer = LongformerTokenizer.from_pretrained("allenai/longformer-base-4096")
    p = pipeline("sentiment-analysis", model=model, tokenizer=tokenizer)
    results = p(text)
    factor = 100 if results[0]['label'] == 'Hawkish' else -100
    return {"label": results[0]['label'], "hawkishness_score": round(results[0]['score'] * factor, 0)}


gr.Interface(predict_fn, "textbox", "label").launch()