Unverified Commit 6ebb66cc authored by BlankR's avatar BlankR Committed by GitHub
Browse files

[Doc] Fix format of multimodal_inputs.md (#31800)


Signed-off-by: default avatarBlankR <hjyblanche@gmail.com>
parent 43d384ba
......@@ -166,16 +166,18 @@ Full example: [examples/offline_inference/vision_language_multi_image.py](../../
If using the [LLM.chat](../models/generative_models.md#llmchat) method, you can pass images directly in the message content using various formats: image URLs, PIL Image objects, or pre-computed embeddings:
```python
from vllm import LLM
from vllm.assets.image import ImageAsset
??? code
llm = LLM(model="llava-hf/llava-1.5-7b-hf")
image_url = "https://picsum.photos/id/32/512/512"
image_pil = ImageAsset('cherry_blossom').pil_image
image_embeds = torch.load(...)
```python
from vllm import LLM
from vllm.assets.image import ImageAsset
conversation = [
llm = LLM(model="llava-hf/llava-1.5-7b-hf")
image_url = "https://picsum.photos/id/32/512/512"
image_pil = ImageAsset('cherry_blossom').pil_image
image_embeds = torch.load(...)
conversation = [
{"role": "system", "content": "You are a helpful assistant"},
{"role": "user", "content": "Hello"},
{"role": "assistant", "content": "Hello! How can I assist you today?"},
......@@ -200,15 +202,15 @@ conversation = [
},
],
},
]
]
# Perform inference and log output.
outputs = llm.chat(conversation)
# Perform inference and log output.
outputs = llm.chat(conversation)
for o in outputs:
for o in outputs:
generated_text = o.outputs[0].text
print(generated_text)
```
```
Multi-image input can be extended to perform video captioning. We show this with [Qwen2-VL](https://huggingface.co/Qwen/Qwen2-VL-2B-Instruct) as it supports videos:
......@@ -893,6 +895,8 @@ The following example demonstrates how to pass image embeddings to the OpenAI se
For Online Serving, you can also skip sending media if you expect cache hits with provided UUIDs. You can do so by sending media like this:
??? code
```python
# Image/video/audio URL:
{
......
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