textgeneration / question_paper.py
Yash Sachdeva
question
d3b2b82
raw
history blame
839 Bytes
import time
import copy
import asyncio
import requests
import transformers
import torch
from fastapi import FastAPI, Request
from transformers import AutoTokenizer
# Load the model
app = FastAPI()
model = "meta-llama/Llama-2-70b"
@app.get("/llama")
def llama():
tokenizer = AutoTokenizer.from_pretrained(model)
pipeline = transformers.pipeline("text-generation" ,model=model ,torch_dtype=torch.float16 ,device_map="auto" , )
sequences = pipeline(
'I liked "Breaking Bad" and "Band of Brothers". Do you have any recommendations of other shows I might like?\n',
do_sample=True,
top_k=10,
num_return_sequences=1,
eos_token_id=tokenizer.eos_token_id,
max_length=200,
)
for seq in sequences:
print(f"Result: {seq['generated_text']}")
return sequences