Enhance dataset card: Add comprehensive metadata and usage examples for KC-MMBench

This PR aims to significantly improve the dataset card for **KC-MMBench** by:

- Adding `video-text-to-text` as the primary task category.
- Including relevant tags such as `multimodal`, `video-understanding`, `short-video`, `benchmark`, `e-commerce`, and `VQA` for enhanced discoverability.
- Updating the `language` tag to include `en` alongside `zh` to reflect the dataset's usage in English-based evaluations and the English documentation/task descriptions.
- Adding `transformers` to `library_name` as the associated models and utilities leverage this library.
- Enriching the dataset description with context from the paper abstract.
- Providing a direct link to the official [Kwai Keye-VL GitHub repository](https://github.com/Kwai-Keye/Kwai-Keye-VL), which contains the evaluation code and usage examples for this benchmark.
- Expanding the "Example of Evaluation" into a comprehensive "Usage" section, incorporating installation instructions and Python code snippets for inference from the GitHub repository, and clearly directing users to the detailed evaluation guide on GitHub.

These updates will make the KC-MMBench dataset easier to find, understand, and utilize for researchers and practitioners on the Hugging Face Hub.

README.md

@@ -1,14 +1,32 @@
 ---
-license: cc-by-sa-4.0
 language:
 - zh
+- en
+license: cc-by-sa-4.0
+task_categories:
+- video-text-to-text
+tags:
+- multimodal
+- video-understanding
+- short-video
+- benchmark
+- e-commerce
+- vqa
+library_name:
+- transformers
 ---
-<font size=3><div align='center' >  [[🍎 Home Page](https://kwai-keye.github.io/)] [[📖 Technical Report](https://huggingface.co/papers/2507.01949)] [[📊 Models](https://huggingface.co/Kwai-Keye)] [[🚀 Demo](https://huggingface.co/spaces/Kwai-Keye/Keye-VL-8B-Preview)] </div></font>
 
+<font size=3><div align='center' >  [[🍎 Home Page](https://kwai-keye.github.io/)] [[📖 Technical Report](https://huggingface.co/papers/2507.01949)] [[\ud83d\udcca Models](https://huggingface.co/Kwai-Keye)] [[\ud83d\ude80 Demo](https://huggingface.co/spaces/Kwai-Keye/Keye-VL-8B-Preview)] </div></font>
+
+This repository contains **KC-MMBench**, a new benchmark dataset meticulously tailored for real-world short-video scenarios, as presented in the paper "[Kwai Keye-VL Technical Report](https://huggingface.co/papers/2507.01949)". Constructed from [Kuaishou](https://www.kuaishou.com/) short video data, KC-MMBench comprises 6 distinct datasets designed to evaluate the performance of Vision-Language Models (VLMs) like [**Kwai Keye-VL-8B**](https://huggingface.co/Kwai-Keye/Keye-VL-8B-Preview), Qwen2.5-VL, and InternVL in comprehending dynamic, information-dense short-form videos.
 
-Based on the [Kuaishou](https://www.kuaishou.com/) short video data, we constructed 6 datasets for Vision-Language Models (VLMs) like [**Kwai Keye-VL-8B**](https://huggingface.co/Kwai-Keye/Keye-VL-8B-Preview), **Qwen2.5-VL** and **InternVL** to evaluate performance.
+For the associated code, detailed documentation, and evaluation scripts, please refer to the official [Kwai Keye-VL GitHub repository](https://github.com/Kwai-Keye/Kwai-Keye-VL).
+
+If you want to use KC-MMbench, please download with:
+```bash
+git clone https://huggingface.co/datasets/Kwai-Keye/KC-MMbench
+```
 
-If you want to use KC-MMbench, please download with: git clone https://huggingface.co/datasets/Kwai-Keye/KC-MMbench 
 ## Tasks
 | Task           | Description                                                                 |
 | -------------- | --------------------------------------------------------------------------- |
@@ -19,7 +37,6 @@ If you want to use KC-MMbench, please download with: git clone https://huggingfa
 | High_Like      | A binary classification task to determine the rate of likes of a short video. |
 | SPU            | The task of determining whether two items are the same product in e-commerce. |
 
-
 ## Performance 
 | Task           | Qwen2.5-VL-3B | Qwen2.5-VL-7B | InternVL-3-8B | MiMo-VL-7B | Kwai Keye-VL-8B |
 | -------------- | ------------- | ------------- | ------------- | ------- | ---- |
@@ -30,13 +47,63 @@ If you want to use KC-MMbench, please download with: git clone https://huggingfa
 | High_Like      | 48.85         | 47.94         | 47.03         | 51.14   | 55.25 |
 | SPU            | 74.09         | 81.34         | 75.64         | 81.86   | 87.05 |
 
-## Example of Evaluation
+## Usage
+
+This section provides a quick guide on how to interact with models using the `keye-vl-utils` library, which is essential for processing and integrating visual language information with Keye Series Models like Kwai Keye-VL-8B.
+
+### Install `keye-vl-utils`
+
+First, install the necessary utility library:
+```bash
+pip install keye-vl-utils
+```
+
+### Keye-VL Inference Example
+
+Here's an example of performing inference with a Kwai Keye-VL model, demonstrating how to prepare inputs for both image and video scenarios.
 
-Here is an example of an evaluation using VLMs on our datasets. The following configuration needs to be added to the config file.
 ```python
-{
+from transformers import AutoModel, AutoProcessor
+from keye_vl_utils import process_vision_info
+
+# default: Load the model on the available device(s)
+model_path = "Kwai-Keye/Keye-VL-8B-Preview"
+
+model = AutoModel.from_pretrained(
+    model_path, torch_dtype="auto", device_map="auto", attn_implementation="flash_attention_2", trust_remote_code=True,
+).to('cuda')
+
+# Example messages demonstrating various input types (image, video)
+messages = [
+    # Image Input Examples
+    [{"role": "user", "content": [{"type": "image", "image": "file:///path/to/your/image.jpg"}, {"type": "text", "text": "Describe this image."}]}],
+    [{"role": "user", "content": [{"type": "image", "image": "http://path/to/your/image.jpg"}, {"type": "text", "text": "Describe this image."}]}],
+    [{"role": "user", "content": [{"type": "image", "image": "data:image;base64,/9j/..."}, {"type": "text", "text": "Describe this image."}]}],
+    
+    # Video Input Examples (most relevant for KC-MMBench)
+    [{"role": "user", "content": [{"type": "video", "video": "file:///path/to/video1.mp4"}, {"type": "text", "text": "Describe this video."}]}],
+    [{"role": "user", "content": [{"type": "video", "video": ["file:///path/to/extracted_frame1.jpg", "file:///path/to/extracted_frame2.jpg", "file:///path/to/extracted_frame3.jpg"],}, {"type": "text", "text": "Describe this video."},],}],
+    [{"role": "user", "content": [{"type": "video", "video": "file:///path/to/video1.mp4", "fps": 2.0, "resized_height": 280, "resized_width": 280}, {"type": "text", "text": "Describe this video."}]}],
+]
+
+processor = AutoProcessor.from_pretrained(model_path)
+# Note: model loaded above already
+text = processor.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+images, videos, video_kwargs = process_vision_info(messages, return_video_kwargs=True)
+inputs = processor(text=text, images=images, videos=videos, padding=True, return_tensors="pt", **video_kwargs).to("cuda")
+generated_ids = model.generate(**inputs)
+print(generated_ids)
+```
 
-    "model":'...'
+### Evaluation
+
+For detailed instructions on how to evaluate models using the KC-MMBench datasets, including setup and running evaluation scripts, please refer to the `evaluation/KC-MMBench/README.md` file in the official [Kwai Keye-VL GitHub repository](https://github.com/Kwai-Keye/Kwai-Keye-VL/tree/main/evaluation/KC-MMBench).
+
+Below is the example configuration for evaluation using VLMs on our datasets:
+
+```python
+{
+    "model": "...", # Specify your model
     "data": {
         "CPV": {
             "class": "KwaiVQADataset",
@@ -64,3 +131,4 @@ Here is an example of an evaluation using VLMs on our datasets. The following co
         }
     }
 }
+```