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源文件 examples/offline_inference/context_extension.py。
# SPDX-License-Identifier: Apache-2.0
from vllm import LLM, SamplingParams
rope_theta = 1000000
original_max_position_embeddings = 32768
factor = 4.0
# Use yarn to extend context
hf_overrides = {
"rope_theta": rope_theta,
"rope_scaling": {
"rope_type": "yarn",
"factor": factor,
"original_max_position_embeddings": original_max_position_embeddings,
},
"max_model_len": int(original_max_position_embeddings * factor),
}
llm = LLM(model="Qwen/Qwen3-0.6B", hf_overrides=hf_overrides)
sampling_params = SamplingParams(
temperature=0.8,
top_p=0.95,
max_tokens=128,
)
conversation = [
{"role": "system", "content": "You are a helpful assistant"},
{"role": "user", "content": "Hello"},
{"role": "assistant", "content": "Hello! How can I assist you today?"},
]
outputs = llm.chat(conversation, sampling_params, use_tqdm=False)
def print_outputs(outputs):
print("\nGenerated Outputs:\n" + "-" * 80)
for output in outputs:
prompt = output.prompt
generated_text = output.outputs[0].text
print(f"Prompt: {prompt!r}\n")
print(f"Generated text: {generated_text!r}")
print("-" * 80)
print_outputs(outputs)