greek-text-summarization
| Property | Value |
|---|---|
| License | Apache 2.0 |
| Downloads | 36,811 |
| Framework | PyTorch |
| Base Architecture | mT5-small |
What is greek-text-summarization?
The greek-text-summarization model is a specialized implementation based on mT5-small, specifically fine-tuned for abstractive text summarization in the Greek language. Developed by kriton, this model has gained significant traction with over 36,000 downloads, demonstrating its utility in the Greek NLP ecosystem.
Implementation Details
The model leverages the Transformers architecture and is built on PyTorch, utilizing the mT5-small as its foundation. It implements a sequence-to-sequence approach for generating concise summaries from longer Greek texts, with support for customizable generation parameters including beam search, length penalties, and repetition prevention.
- Built on the mT5-small architecture
- Implements custom generation parameters for optimal summarization
- Supports max_length of 1024 tokens for input
- Generates summaries with configurable length constraints
Core Capabilities
- Abstractive summarization of Greek text
- Customizable summary length and generation parameters
- Production-ready with Hugging Face Spaces deployment
- Efficient processing of long-form content
Frequently Asked Questions
Q: What makes this model unique?
This model stands out as a specialized solution for Greek language summarization, filling a crucial gap in Greek NLP capabilities. Its implementation on mT5-small provides a balance between performance and resource efficiency.
Q: What are the recommended use cases?
The model is ideal for automated summarization of Greek news articles, documents, and content where concise summaries are needed. It's particularly useful for content management systems, news aggregators, and research applications dealing with Greek text.
