[Doc] Fix VLM prompt placeholder sample bug (vllm-project#9170)

Signed-off-by: Sumit Dubey <sumit.dubey2@ibm.com>

Author: ycool

docs/source/models/vlm.rst

@@ -25,7 +25,7 @@ The :class:`~vllm.LLM` class can be instantiated in much the same way as languag
 To pass an image to the model, note the following in :class:`vllm.inputs.PromptType`:
 
 * ``prompt``: The prompt should follow the format that is documented on HuggingFace.
-* ``multi_modal_data``: This is a dictionary that follows the schema defined in :class:`vllm.multimodal.MultiModalDataDict`. 
+* ``multi_modal_data``: This is a dictionary that follows the schema defined in :class:`vllm.multimodal.MultiModalDataDict`.
 
 .. code-block:: python
 
@@ -34,7 +34,7 @@ To pass an image to the model, note the following in :class:`vllm.inputs.PromptT
 
     # Load the image using PIL.Image
     image = PIL.Image.open(...)
-    
+
     # Single prompt inference
     outputs = llm.generate({
         "prompt": prompt,
@@ -68,7 +68,7 @@ To pass an image to the model, note the following in :class:`vllm.inputs.PromptT
         "prompt": prompt,
         "multi_modal_data": mm_data,
     })
-    
+
     for o in outputs:
         generated_text = o.outputs[0].text
         print(generated_text)
@@ -116,7 +116,7 @@ Instead of passing in a single image, you can pass in a list of images.
 .. code-block:: python
 
     # Refer to the HuggingFace repo for the correct format to use
-    prompt = "<|user|>\n<image_1>\n<image_2>\nWhat is the content of each image?<|end|>\n<|assistant|>\n"
+    prompt = "<|user|>\n<|image_1|>\n<|image_2|>\nWhat is the content of each image?<|end|>\n<|assistant|>\n"
 
     # Load the images using PIL.Image
     image1 = PIL.Image.open(...)
@@ -135,11 +135,11 @@ 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: 
+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. 
+    # 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.
@@ -157,7 +157,7 @@ Multi-image input can be extended to perform video captioning. We show this with
 
     # Perform inference and log output.
     outputs = llm.chat([message])
-    
+
     for o in outputs:
         generated_text = o.outputs[0].text
         print(generated_text)