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import transformers | |
import torch | |
import os | |
from fastapi import FastAPI | |
from transformers import AutoTokenizer | |
# Load the model | |
app = FastAPI() | |
model = "meta-llama/Llama-2-7b-hf" | |
access_token = os.getenv("access_token") | |
def llama(): | |
tokenizer = AutoTokenizer.from_pretrained(model,token=access_token) | |
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("Result: {seq['generated_text']}") | |
return {"output": sequences[0]["generated_text"]} | |