intent-model
| Property | Value |
|---|---|
| License | MIT |
| Base Model | DistilBERT-base-uncased |
| Framework | Keras, TensorFlow |
| Language | English |
What is intent-model?
The intent-model is a specialized multiclass classifier built on top of DistilBERT, designed specifically for the Danswer question-answering system. It serves as an intelligent query interpreter that categorizes user inputs into three distinct categories: Keyword Search, Semantic Search, and Direct Question Answering. This classification is crucial for determining the most appropriate search strategy for each user query.
Implementation Details
Built using the DistilBERT architecture and implemented with Keras and TensorFlow, this model provides efficient query intent classification. It utilizes transformer-based language understanding capabilities while maintaining computational efficiency through distillation techniques.
- Built on DistilBERT-base-uncased architecture
- Implements three-way classification for query processing
- Integrated with the Danswer QA system ecosystem
- Optimized for English language queries
Core Capabilities
- Accurate classification of user queries into three distinct categories
- Real-time query intent analysis
- Seamless integration with larger QA systems
- Efficient processing through distilled architecture
Frequently Asked Questions
Q: What makes this model unique?
This model is specifically designed for the Danswer project's query processing pipeline, offering specialized intent classification that helps optimize the search and answer retrieval process. Its three-way classification system is particularly suited for enterprise search and QA applications.
Q: What are the recommended use cases?
The model is primarily intended for integration with the Danswer Question-Answering System. It's particularly useful for organizations looking to implement intelligent query processing in their search systems, especially those requiring differentiation between keyword searches, semantic searches, and direct questions.
