app.py

#from fastapi import FastAPI
from flask import Flask
from transformers import GPT2LMHeadModel, GPT2Tokenizer
import numpy as np 

#app = FastAPI()
app = Flask(__name__)

model = GPT2LMHeadModel.from_pretrained('gpt2')
tokenizer = GPT2Tokenizer.from_pretrained('gpt2')

@app.get("/score/<text>")
def score(text):
    tokens_tensor = tokenizer.encode( text, add_special_tokens=False, return_tensors="pt")
    loss=model(tokens_tensor, labels=tokens_tensor)[0]
    print(text,loss)
    return str(np.exp(loss.cpu().detach().numpy()))

#sentence = st.text_input("Enter the sentence","this is a well formed sentence.")
#res = score(sentence)
#st.write('score is', res)

if __name__ == "__main__":
    app.run(debug=True)