7f00899ff7
Signed-off-by: reidliu41 <reid201711@gmail.com> Co-authored-by: reidliu41 <reid201711@gmail.com>
38 lines
1.2 KiB
Python
38 lines
1.2 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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from vllm import LLM, SamplingParams
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prompts = [
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"A robot may not injure a human being",
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"It is only with the heart that one can see rightly;",
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"The greatest glory in living lies not in never falling,",
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]
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answers = [
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" or, through inaction, allow a human being to come to harm.",
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" what is essential is invisible to the eye.",
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" but in rising every time we fall.",
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]
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N = 1
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# Currently, top-p sampling is disabled. `top_p` should be 1.0.
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sampling_params = SamplingParams(temperature=0, top_p=1.0, n=N, max_tokens=16)
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def main():
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# Set `enforce_eager=True` to avoid ahead-of-time compilation.
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# In real workloads, `enforace_eager` should be `False`.
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llm = LLM(model="Qwen/Qwen2-1.5B-Instruct",
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max_num_batched_tokens=64,
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max_num_seqs=4)
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outputs = llm.generate(prompts, sampling_params)
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print("-" * 50)
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for output, answer in zip(outputs, answers):
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prompt = output.prompt
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generated_text = output.outputs[0].text
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print(f"Prompt: {prompt!r}\nGenerated text: {generated_text!r}")
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assert generated_text.startswith(answer)
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print("-" * 50)
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if __name__ == "__main__":
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main()
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