Skip to content
Merged
Changes from 6 commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
26 changes: 26 additions & 0 deletions docs/source/models/vlm.rst
Original file line number Diff line number Diff line change
Expand Up @@ -135,6 +135,32 @@ Instead of passing in a single image, you can pass in a list of images.

A code example can be found in `examples/offline_inference_vision_language_multi_image.py <https://github.com/vllm-project/vllm/blob/main/examples/offline_inference_vision_language_multi_image.py>`_.

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:

.. code-block:: python
# Specify the maximum number of frames per video to be 4. This can be changed.
llm = LLM("Qwen/Qwen2-VL-2B-Instruct", limit_mm_per_prompt={"image": 4})

# Create the request payload.
video_frames = ... # load your video making sure it only has the number of frames specified earlier.
message = {
"role": "user",
"content": [
{"type": "text", "text": "Describe this set of frames. Consider the frames to be a part of the same video."},
],
}
for i in range(len(video_frames)):
base64_image = encode_image(video_frames[i]) # base64 encoding.
new_image = {"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{base64_image}"}}
message["content"].append(new_image)

# Perform inference and log output.
outputs = llm.chat([message])

for o in outputs:
generated_text = o.outputs[0].text
print(generated_text)

Online Inference
----------------

Expand Down
Loading