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- # Copyright (c) Meta Platforms, Inc. and affiliates.
- # This software may be used and distributed according to the terms of the Llama 2 Community License Agreement.
- import fire
- import torch
- from vllm import LLM
- from vllm import LLM, SamplingParams
- from accelerate.utils import is_xpu_available
- if is_xpu_available():
- torch.xpu.manual_seed(42)
- else:
- torch.cuda.manual_seed(42)
- torch.manual_seed(42)
- def load_model(model_name, tp_size=1):
- llm = LLM(model_name, tensor_parallel_size=tp_size)
- return llm
- def main(
- model,
- max_new_tokens=100,
- user_prompt=None,
- top_p=0.9,
- temperature=0.8
- ):
- while True:
- if user_prompt is None:
- user_prompt = input("Enter your prompt: ")
-
- print(f"User prompt:\n{user_prompt}")
- print(f"sampling params: top_p {top_p} and temperature {temperature} for this inference request")
- sampling_param = SamplingParams(top_p=top_p, temperature=temperature, max_tokens=max_new_tokens)
-
- outputs = model.generate(user_prompt, sampling_params=sampling_param)
-
- print(f"model output:\n {user_prompt} {outputs[0].outputs[0].text}")
- user_prompt = input("Enter next prompt (press Enter to exit): ")
- if not user_prompt:
- break
- def run_script(
- model_name: str,
- peft_model=None,
- tp_size=1,
- max_new_tokens=100,
- user_prompt=None,
- top_p=0.9,
- temperature=0.8
- ):
- model = load_model(model_name, tp_size)
- main(model, max_new_tokens, user_prompt, top_p, temperature)
- if __name__ == "__main__":
- fire.Fire(run_script)
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