mt5-small-turkish-squad
| Property | Value |
|---|---|
| Model Size | 300M parameters |
| License | MIT |
| Framework | PyTorch |
| Dataset | TQUAD |
What is mt5-small-turkish-squad?
mt5-small-turkish-squad is a specialized question-answering model based on Google's Multilingual T5-small architecture, specifically fine-tuned for Turkish language processing. This model represents a significant advancement in Turkish natural language processing, utilizing the powerful mT5 architecture with 300 million parameters fine-tuned on the Turkish Question Answering dataset (TQUAD).
Implementation Details
The model is implemented using PyTorch Lightning and requires about 1.2GB of storage. It's designed as a sequence-to-sequence model that can process input contexts up to 512 tokens and generate answers up to 120 tokens in length.
- Built on mT5-small architecture (300M parameters)
- Fine-tuned specifically for Turkish Q&A tasks
- Implements sequence-to-sequence learning approach
- Utilizes PyTorch Lightning for efficient training
Core Capabilities
- Turkish language question answering
- Context-based response generation
- Handles long-form text input (up to 512 tokens)
- Efficient processing for real-time applications
Frequently Asked Questions
Q: What makes this model unique?
This model is the first implementation of mT5-small specifically optimized for Turkish question answering, offering a balance between performance and resource efficiency with its 300M parameter architecture.
Q: What are the recommended use cases?
The model is ideal for Turkish language applications requiring question answering capabilities, such as chatbots, educational tools, and information extraction systems working with Turkish text.
