Create README.md

README.md

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+---
+license: mit
+language:
+- en
+tags:
+- dataset
+- document-processing
+- multimodal
+- vision-language
+- information-retrieval
+
+---
+
+# 📊 Banque_Vision: A Multimodal Dataset for Document Understanding
+
+## 📌 Overview
+**Banque_Vision** is a **multimodal dataset** designed for **document-based question answering (QA) and information retrieval**. It combines **textual data** and **visual document representations**, enabling research on **how vision models and language models** interact for document comprehension.
+
+🔗 **Created by**: Matteo Khan   
+🎓 **Affiliation**: TW3Partners 
+📍 **License**: MIT  
+
+🔗 [Connect with me on LinkedIn](https://www.linkedin.com/in/matteo-khan-a10309263/)  
+🔗 [Dataset on Hugging Face](https://huggingface.co/datasets/YourProfile/banque_vision)  
+
+## 📂 Dataset Structure
+- **Query**: The question or request for information.
+- **Document Text**: The full text of the document related to the query.
+- **Document Page**: The specific page containing the answer.
+- **Document Image**: The visual representation (scan or screenshot) of the document page.
+- **Answer**: The extracted response based on the query.
+
+This dataset allows models to process and retrieve information across both textual and visual modalities, making it highly relevant for **document AI research**.
+
+## 🎯 Intended Use
+This dataset is designed for:
+- ✅ **Document-based QA** (e.g., answering questions based on scanned documents)
+- ✅ **Information retrieval** from structured/unstructured sources
+- ✅ **Multimodal learning** for combining text and vision-based features
+- ✅ **OCR-based research** and benchmarking
+- ✅ **Fine-tuning vision-language models** like Donut, LayoutLM, and BLIP
+
+## ⚠️ Limitations & Considerations
+While **Banque_Vision** is a powerful resource, users should be aware of:
+- ❌ **OCR errors**: Text extraction may be imperfect due to document quality.
+- ⚠️ **Bias in document sources**: Some domains may be over- or under-represented.
+- 🔄 **Data labeling noise**: Possible inaccuracies in question-answer alignment.
+
+## 📊 Dataset Format
+The dataset is stored in **JSONL** format with the following structure:
+
+```json
+{
+  "query": "What is the interest rate for savings accounts?",
+  "document_text": "... The standard interest rate for savings accounts is 2.5% ...",
+  "document_page": 5,
+  "document_image": "path/to/image.jpg",
+  "answer": "2.5%"
+}
+```
+
+## 🚀 How to Use
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("YourProfile/banque_vision")
+
+# Example
+sample = dataset["train"][0]
+print("Query:", sample["query"])
+print("Answer:", sample["answer"])
+```
+
+## 🌍 Why It Matters
+- **Bridges the gap** between text and vision-based document processing.
+- **Supports real-world applications** like legal document analysis, financial records processing, and automated document retrieval.
+- **Encourages innovation** in hybrid models that combine **LLMs with vision transformers**.
+
+## 📝 Citation
+```bibtex
+@misc{banquevision2025,
+      title={Banque_Vision: A Multimodal Dataset for Document Understanding},
+      author={Your Name},
+      year={2025},
+      eprint={arXiv:XXXX.XXXXX},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```
+
+📩 **Feedback & Contributions**: Feel free to collaborate or provide feedback via [Hugging Face](https://huggingface.co/datasets/YourProfile/banque_vision).
+
+🎉 **Happy Researching!** 🚀
+