|
from ctransformers import AutoModelForCausalLM |
|
from fastapi import FastAPI, Form |
|
from pydantic import BaseModel |
|
|
|
|
|
llm = AutoModelForCausalLM.from_pretrained("victunes/TherapyBeagle-11B-v1-GGUF", |
|
model_type='llama', |
|
max_new_tokens = 1096, |
|
threads = 3, |
|
) |
|
|
|
|
|
|
|
class validation(BaseModel): |
|
prompt: str |
|
|
|
|
|
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.strip()}{E_INST}\n{assistant}\n" |
|
return llm(prompt) |
|
|