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86ae693f20
Signed-off-by: DarkLight1337 <tlleungac@connect.ust.hk> Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com> Co-authored-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
53 lines
1.4 KiB
Python
53 lines
1.4 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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from argparse import Namespace
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from vllm import LLM, EngineArgs
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from vllm.utils import FlexibleArgumentParser
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def parse_args():
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parser = FlexibleArgumentParser()
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parser = EngineArgs.add_cli_args(parser)
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# Set example specific arguments
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parser.set_defaults(
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model="jason9693/Qwen2.5-1.5B-apeach",
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runner="pooling",
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enforce_eager=True,
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)
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return parser.parse_args()
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def main(args: Namespace):
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# Sample prompts.
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prompts = [
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"Hello, my name is",
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"The president of the United States is",
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"The capital of France is",
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"The future of AI is",
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]
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# Create an LLM.
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# You should pass runner="pooling" for classification models
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llm = LLM(**vars(args))
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# Generate logits. The output is a list of ClassificationRequestOutputs.
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outputs = llm.classify(prompts)
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# Print the outputs.
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print("\nGenerated Outputs:\n" + "-" * 60)
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for prompt, output in zip(prompts, outputs):
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probs = output.outputs.probs
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probs_trimmed = (str(probs[:16])[:-1] + ", ...]") if len(probs) > 16 else probs
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print(
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f"Prompt: {prompt!r} \n"
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f"Class Probabilities: {probs_trimmed} (size={len(probs)})"
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)
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print("-" * 60)
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if __name__ == "__main__":
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args = parse_args()
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main(args)
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