|
|
--- |
|
|
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 |
