question_paper.py

import transformers
import torch

from fastapi import FastAPI

from transformers import AutoModelForCausalLM, AutoTokenizer

app = FastAPI()

MODEL = None
TOKENIZER = None

@app.get("/")
def llama():
    text = "Hi, my name is "
    inputs = TOKENIZER(text, return_tensors="pt").input_ids
    outputs = MODEL.generate(
        inputs,
        max_length=256,
        pad_token_id=TOKENIZER.pad_token_id,
        eos_token_id=TOKENIZER.eos_token_id,
    )
    tresponse = TOKENIZER.decode(outputs[0], skip_special_tokens=True)
    print(tresponse)

    return tresponse

@app.on_event("startup")
def init_model():
    global MODEL
    global TOKENIZER
    if not MODEL:
        print("loading model")
        TOKENIZER = AutoTokenizer.from_pretrained("berkeley-nest/Starling-LM-7B-alpha")
        MODEL = AutoModelForCausalLM.from_pretrained("berkeley-nest/Starling-LM-7B-alpha")
        print("loaded model")