vidore_benchmark_qa_dummy

## Dataset Description
This dataset is a small subset of the [`vidore/syntheticDocQA_energy_test`](https://huggingface.co/datasets/vidore/syntheticDocQA_energy_test) dataset.
It aims to be used for debugging and testing.

### Load the dataset

```python
from datasets import load_dataset
ds = load_dataset("vidore/vidore_benchmark_qa_dummy", split="test")
```

### Dataset Structure

Here is an example of a dataset instance structure:

```json
features:
- name: query
dtype: string
- name: image
dtype: image
- name: image_filename
dtype: string
- name: answer
dtype: string
- name: page
dtype: string
- name: model
dtype: string
- name: prompt
dtype: string
- name: source
dtype: string
```

## Citation Information

If you use this dataset in your research, please cite the original dataset as follows:

```latex
@misc{faysse2024colpaliefficientdocumentretrieval,
title={ColPali: Efficient Document Retrieval with Vision Language Models},
author={Manuel Faysse and Hugues Sibille and Tony Wu and Gautier Viaud and Céline Hudelot and Pierre Colombo},
year={2024},
eprint={2407.01449},
archivePrefix={arXiv},
primaryClass={cs.IR},
url={https://arxiv.org/abs/2407.01449},
}
```

## 数据集描述
本数据集是 [`vidore/syntheticDocQA_energy_test`](https://huggingface.co/datasets/vidore/syntheticDocQA_energy_test) 数据集的小型子集，旨在用于调试与测试。

### 数据集加载
可通过如下Python代码加载该数据集：
python
from datasets import load_dataset
ds = load_dataset("vidore/vidore_benchmark_qa_dummy", split="test")

### 数据集结构
以下为数据集实例的结构示例：
json
- 字段名：查询文本 (query)，数据类型：字符串
- 字段名：图像 (image)，数据类型：图像
- 字段名：图像文件名 (image_filename)，数据类型：字符串
- 字段名：答案 (answer)，数据类型：字符串
- 字段名：页码 (page)，数据类型：字符串
- 字段名：模型 (model)，数据类型：字符串
- 字段名：提示词 (prompt)，数据类型：字符串
- 字段名：来源 (source)，数据类型：字符串

## 引用信息
若您在研究工作中使用本数据集，请按如下格式引用其原始数据集：
latex
@misc{faysse2024colpaliefficientdocumentretrieval,
title={ColPali: Efficient Document Retrieval with Vision Language Models},
author={Manuel Faysse and Hugues Sibille and Tony Wu and Gautier Viaud and Céline Hudelot and Pierre Colombo},
year={2024},
eprint={2407.01449},
archivePrefix={arXiv},
primaryClass={cs.IR},
url={https://arxiv.org/abs/2407.01449},
}