[doc] Fold long code blocks to improve readability (#19926)

Signed-off-by: reidliu41 <reid201711@gmail.com>
Co-authored-by: reidliu41 <reid201711@gmail.com>
This commit is contained in:
Reid
2025-06-23 13:24:23 +08:00
committed by GitHub
parent 493c275352
commit f17aec0d63
50 changed files with 3455 additions and 3180 deletions

View File

@@ -85,35 +85,37 @@ and automatically applies the model's [chat template](https://huggingface.co/doc
In general, only instruction-tuned models have a chat template.
Base models may perform poorly as they are not trained to respond to the chat conversation.
```python
from vllm import LLM
??? Code
llm = LLM(model="meta-llama/Meta-Llama-3-8B-Instruct")
conversation = [
{
"role": "system",
"content": "You are a helpful assistant"
},
{
"role": "user",
"content": "Hello"
},
{
"role": "assistant",
"content": "Hello! How can I assist you today?"
},
{
"role": "user",
"content": "Write an essay about the importance of higher education.",
},
]
outputs = llm.chat(conversation)
```python
from vllm import LLM
for output in outputs:
prompt = output.prompt
generated_text = output.outputs[0].text
print(f"Prompt: {prompt!r}, Generated text: {generated_text!r}")
```
llm = LLM(model="meta-llama/Meta-Llama-3-8B-Instruct")
conversation = [
{
"role": "system",
"content": "You are a helpful assistant"
},
{
"role": "user",
"content": "Hello"
},
{
"role": "assistant",
"content": "Hello! How can I assist you today?"
},
{
"role": "user",
"content": "Write an essay about the importance of higher education.",
},
]
outputs = llm.chat(conversation)
for output in outputs:
prompt = output.prompt
generated_text = output.outputs[0].text
print(f"Prompt: {prompt!r}, Generated text: {generated_text!r}")
```
A code example can be found here: <gh-file:examples/offline_inference/basic/chat.py>