[doc] Fold long code blocks to improve readability (#19926)
Signed-off-by: reidliu41 <reid201711@gmail.com> Co-authored-by: reidliu41 <reid201711@gmail.com>
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@@ -85,35 +85,37 @@ and automatically applies the model's [chat template](https://huggingface.co/doc
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In general, only instruction-tuned models have a chat template.
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Base models may perform poorly as they are not trained to respond to the chat conversation.
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```python
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from vllm import LLM
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??? Code
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llm = LLM(model="meta-llama/Meta-Llama-3-8B-Instruct")
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conversation = [
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{
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"role": "system",
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"content": "You are a helpful assistant"
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},
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{
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"role": "user",
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"content": "Hello"
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},
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{
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"role": "assistant",
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"content": "Hello! How can I assist you today?"
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},
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{
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"role": "user",
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"content": "Write an essay about the importance of higher education.",
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},
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]
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outputs = llm.chat(conversation)
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```python
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from vllm import LLM
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for output in outputs:
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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}, Generated text: {generated_text!r}")
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```
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llm = LLM(model="meta-llama/Meta-Llama-3-8B-Instruct")
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conversation = [
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{
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"role": "system",
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"content": "You are a helpful assistant"
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},
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{
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"role": "user",
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"content": "Hello"
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},
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{
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"role": "assistant",
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"content": "Hello! How can I assist you today?"
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},
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{
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"role": "user",
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"content": "Write an essay about the importance of higher education.",
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},
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]
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outputs = llm.chat(conversation)
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for output in outputs:
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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}, Generated text: {generated_text!r}")
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```
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A code example can be found here: <gh-file:examples/offline_inference/basic/chat.py>
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