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from fastapi import FastAPI
from pydantic import BaseModel
from transformers import pipeline
import os
from huggingface_hub import login
# Log in to Hugging Face
access_token = os.environ.get("ACCESS_TOKEN_1")
login(token=access_token)
app = FastAPI()
# Load the model and tokenizer from the Hugging Face Hub
model_name = "MHULO/yembaner"
nlp = pipeline("ner", model=model_name, tokenizer=model_name)
class TextRequest(BaseModel):
text: str
@app.post("/predict/")
def predict(request: TextRequest):
ner_results = nlp(request.text)
return ner_results
if __name__ == "__main__":
import uvicorn
uvicorn.run(app, host="0.0.0.0", port=8000)
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