Update README.md

README.md

@@ -9,4 +9,41 @@ metrics:
 base_model:
 - FacebookAI/xlm-roberta-large
 pipeline_tag: question-answering
----
+---
+
+# NamSyntax/xlmr-large-viquad
+
+## Model Description
+**NamSyntax/xlmr-large-viquad** is a fine-tuned version of the **XLM-RoBERTa Large** model for Vietnamese Question Answering (QA). It was meticulously fine-tuned on the [UIT-ViQuAD 2.0](https://huggingface.co/datasets/taidng/UIT-ViQuAD2.0) dataset to deliver precise, context-aware answers. 
+
+This model is a part of the [Vietnamese-QA](https://github.com/NamSyntax/Vietnamese-QA) end-to-end Machine Learning pipeline project. (“If you find this repo helpful, feel free to give it a star ⭐—it really means a lot!”)
+
+## Intended Uses
+- **Primary Use:** Extractive Question Answering in Vietnamese. Given a context paragraph and a question, the model extracts the substring representing the answer from the context.
+- **Ecosystem:** It can be instantly integrated into web services. The associated project provides out-of-the-box support for a **Gradio Web UI** and a **FastAPI** REST backend.
+
+## Training Data
+The model was fine-tuned on **UIT-ViQuAD 2.0**, a high-quality machine reading comprehension dataset curated specifically for the Vietnamese language. 
+
+## Training Procedure
+This model was trained using PyTorch and the Hugging Face `Trainer` API. The training pipeline implements:
+- Clean modular architecture for HuggingFace Dataset loading.
+- Preprocessing steps emphasizing text tokenization and chunking logic to handle long documents.
+- Hyperparameter management via `config.yaml`.
+
+## How to use
+You can use this model directly with the `pipeline` API from Hugging Face:
+
+```python
+from transformers import pipeline
+
+qa_pipeline = pipeline("question-answering", model="NamSyntax/xlmr-large-viquad")
+
+context = "Hà Nội là thủ đô của nước Cộng hòa Xã hội chủ nghĩa Việt Nam. Thành phố nằm ở phía tây bắc trung tâm vùng đồng bằng châu thổ sông Hồng."
+question = "Thủ đô của Việt Nam là gì?"
+
+result = qa_pipeline(question=question, context=context)
+print(result)
+```
+
+Alternatively, to experience this model with an interactive UI or to deploy it as a production-grade backend service (FastAPI and Docker), please refer to the official repository: [NamSyntax/Vietnamese-QA](https://github.com/NamSyntax/Vietnamese-QA).