Create README.md

README.md

@@ -0,0 +1,38 @@
+---
+language: fa
+tags:
+- parsbert
+- bert
+- question-answering
+- nlp
+license: mit
+base_model: hooshvare/parsbert-base-uncased
+---
+
+# PQuAD: Persian Question Answering Model
+
+This model is a fine-tuned version of **[ParsBERT](https://huggingface.co/hooshvare/parsbert-base-uncased)** (state-of-the-art Persian language model) for the task of **Question Answering**.
+
+It was trained on a proprietary Persian QA dataset as part of a BSc thesis at **Amirkabir University of Technology**.
+
+## Model Details
+- **Base Model:** ParsBERT (Hooshvare Lab)
+- **Task:** Extractive Question Answering
+- **Language:** Persian (Farsi)
+- **Framework:** PyTorch & Transformers
+
+## How to Use
+You can use this model directly with the Hugging Face `pipeline`:
+
+```python
+from transformers import pipeline
+
+# Load the pipeline
+qa_pipeline = pipeline("question-answering", model="newsha/PQuAD")
+
+context = "دانشگاه صنعتی امیرکبیر یکی از با‌سابقه‌ترین دانشگاه‌های فنی ایران است که در سال ۱۳۳۷ در تهران تأسیس شد."
+question = "دانشگاه امیرکبیر در چه سالی تأسیس شد؟"
+
+result = qa_pipeline(question=question, context=context)
+print(f"Answer: {result['answer']}")
+# Output: ۱۳۳۷