Randeng-BART-139M-SUMMARY
| Property | Value |
|---|---|
| Parameter Count | 139M |
| Model Type | BART-base |
| Architecture | Chinese BART for Summarization |
| Developer | IDEA-CCNL |
| Paper | Fengshenbang 1.0 |
What is Randeng-BART-139M-SUMMARY?
Randeng-BART-139M-SUMMARY is a specialized Chinese language model based on BART architecture, specifically fine-tuned for text summarization tasks. It's part of the Fengshenbang series developed by IDEA-CCNL, trained on the LCSTS (Large-scale Chinese Short Text Summarization) dataset to provide accurate and concise summaries of Chinese text.
Implementation Details
The model is implemented using the transformers library and builds upon the base Randeng-BART-139M architecture. It utilizes conditional generation capabilities to produce summarized output from input text, with specific optimizations for Chinese language processing.
- Built on BART-base architecture with 139M parameters
- Fine-tuned specifically for Chinese summarization tasks
- Implements Text2TextGenerationPipeline for easy inference
- Optimized for the LCSTS dataset
Core Capabilities
- Efficient Chinese text summarization
- Natural language transformation (NLT)
- Conditional text generation
- Support for variable-length output generation
Frequently Asked Questions
Q: What makes this model unique?
This model's uniqueness lies in its specialized fine-tuning for Chinese text summarization, making it particularly effective for condensing Chinese content while maintaining semantic accuracy. Its integration into the Fengshenbang ecosystem provides robust support for Chinese NLP applications.
Q: What are the recommended use cases?
The model is best suited for applications requiring Chinese text summarization, such as news article condensation, document summarization, and content briefing systems. It's particularly effective for scenarios requiring automated generation of concise Chinese language summaries from longer texts.
