29 lines
786 B
Python
29 lines
786 B
Python
from vllm import LLM
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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 task="classify" for classification models
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model = LLM(
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model="jason9693/Qwen2.5-1.5B-apeach",
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task="classify",
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enforce_eager=True,
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)
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# Generate logits. The output is a list of ClassificationRequestOutputs.
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outputs = model.classify(prompts)
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# Print the outputs.
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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] +
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", ...]") if len(probs) > 16 else probs)
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print(f"Prompt: {prompt!r} | "
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f"Class Probabilities: {probs_trimmed} (size={len(probs)})")
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