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| from fastapi import FastAPI, Request | |
| from transformers import pipeline | |
| from pydantic import BaseModel | |
| class TextQuery(BaseModel): | |
| inputs: str | |
| def predict(text: str): | |
| model_name = "blanchefort/rubert-base-cased-sentiment-rurewiews" | |
| pipe = pipeline("text-classification", model=model_name, return_all_scores=True) | |
| scores = pipe(text)[0] | |
| sorted_scores = sorted(scores, key=lambda x: x['score'], reverse=True) | |
| return sorted_scores | |
| app = FastAPI() | |
| def home(request: Request, q: TextQuery): | |
| return predict(q.inputs) | |