LTP Small Model
| Property | Value |
|---|---|
| Paper | N-LTP: A Open-source Neural Chinese Language Technology Platform |
| Framework | PyTorch |
| Downloads | 226,606 |
| Processing Speed | 43.13 sentences/second |
What is LTP Small?
LTP Small is a compact version of the Language Technology Platform (LTP), a comprehensive Chinese natural language processing toolkit. It provides efficient performance while maintaining high accuracy across six fundamental NLP tasks, making it an excellent choice for production environments where balance between speed and accuracy is crucial.
Implementation Details
Built on PyTorch, LTP Small delivers impressive performance metrics across core NLP tasks: 98.4% accuracy in word segmentation, 98.2% in POS tagging, 94.3% in named entity recognition, 78.4% in semantic role labeling, 88.3% in dependency parsing, and 74.7% in semantic dependency parsing.
- Optimized architecture for efficient processing
- Supports both CPU and GPU acceleration
- Implements modern deep learning approaches
- Provides simple Pipeline API for easy integration
Core Capabilities
- Chinese word segmentation (CWS)
- Part-of-speech (POS) tagging
- Named Entity Recognition (NER)
- Semantic Role Labeling (SRL)
- Dependency Parsing
- Semantic Dependency Parsing
Frequently Asked Questions
Q: What makes this model unique?
LTP Small stands out for its balanced performance profile, offering near-state-of-the-art accuracy while maintaining faster processing speeds than larger models. It processes 43.13 sentences per second while maintaining high accuracy across all tasks.
Q: What are the recommended use cases?
The model is ideal for production environments where processing speed is important but accuracy cannot be significantly compromised. It's particularly suitable for applications in text analysis, information extraction, and general Chinese NLP tasks requiring real-time processing.
