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import os
from ctransformers import AutoModelForCausalLM
from fastapi import FastAPI
from pydantic import BaseModel
import requests
from huggingface_hub import hf_hub_download
file_name = "zephyr-7b-beta.Q4_K_S.gguf"
if not os.path.exists(file_name):
hf_hub_download("TheBloke/zephyr-7B-beta-GGUF", filename=file_name, local_dir=f"./")
llm = AutoModelForCausalLM.from_pretrained(file_name,
model_type='mistral',
max_new_tokens = 1096,
threads = 3,
)
#Pydantic object
class validation(BaseModel):
prompt: str
#Fast API
app = FastAPI()
@app.post("/llm_on_cpu")
async def stream(item: validation):
system_prompt = 'Below is an instruction that describes a task. Write a response that appropriately completes the request.'
E_INST = "</s>"
user, assistant = "<|user|>", "<|assistant|>"
prompt = f"{system_prompt}{E_INST}\n{user}\n{item.prompt}{E_INST}\n{assistant}\n"
# return llm(prompt)
return prompt |