xlm-roberta-large-fa-qa
| Property | Value |
|---|---|
| Author | SajjadAyoubi |
| Model Type | Question Answering |
| Language | Persian (Farsi) |
| Base Architecture | XLM-RoBERTa Large |
What is xlm-roberta-large-fa-qa?
xlm-roberta-large-fa-qa is a specialized question-answering model built on the XLM-RoBERTa large architecture, specifically fine-tuned for Persian language queries. This model enables accurate extraction of answers from given contexts in Farsi, supporting both pipeline and manual implementation approaches.
Implementation Details
The model can be implemented using either the Transformers pipeline for quick deployment or a manual approach for more control. It supports both PyTorch and TensorFlow 2.X frameworks, offering flexibility in integration. The manual approach provides additional capabilities, including the ability to handle no-answer scenarios and improved performance metrics.
- Supports both pipeline and manual implementation approaches
- Compatible with PyTorch and TensorFlow 2.X
- Includes custom AnswerPredictor utilities for enhanced control
- Requires transformers and sentencepiece dependencies
Core Capabilities
- Persian language question answering with high accuracy
- Batch processing support
- Confidence score generation for answers
- Flexible answer span detection
- Support for no-answer scenarios in manual mode
Frequently Asked Questions
Q: What makes this model unique?
This model specializes in Persian language question-answering tasks, leveraging the powerful XLM-RoBERTa architecture while providing flexible implementation options and robust answer prediction capabilities.
Q: What are the recommended use cases?
The model is ideal for Persian language applications requiring question answering capabilities, including chatbots, information extraction systems, and automated customer service solutions. It's particularly effective when precise answer extraction from given contexts is needed.
