ERNIE-4.0-8K
- 8K Context
- 5.48/M Input Tokens
- 16.44/M Output Tokens
- Ernie
- Text 2 text
- 17 Nov, 2024
Model Unavailable
Developer/Company: Baidu Research
Key Capabilities & Use Cases: ERNIE-4.0-8K is valuable in natural language processing (NLP), applicable to search engines, intelligent customer service, content recommendation, and sentiment analysis.
Features & Improvements:
- Multi-task Learning: Supports tasks like text classification, sentiment analysis, and named entity recognition.
- Knowledge Enhancement: Incorporates knowledge graphs to boost domain-specific performance.
- Cross-lingual Capability: Handles multiple languages effectively.
- Explainability: Provides visualization for understanding model decisions.
Technical Specifications: Utilizes an 8K word embedding dimension for precise language nuance capture.
Performance Characteristics:
- High 8K word embedding dimension.
- Enhanced cross-language and knowledge processing capabilities.
- Focus on model explainability.
Target Applications/Industries: Suitable for industries requiring advanced semantic understanding and multilingual support, such as search, customer service, and content recommendation systems.