mmarco-mMiniLMv2-L6-H384-v1
| Property | Value |
|---|---|
| Author | nreimers |
| Model Type | Multilingual Text Embeddings |
| Architecture | MiniLMv2 (6 layers, 384 hidden size) |
| Model Link | Hugging Face |
What is mmarco-mMiniLMv2-L6-H384-v1?
mmarco-mMiniLMv2-L6-H384-v1 is a multilingual version of the MiniLM architecture, specifically designed for cross-lingual information retrieval and semantic search applications. This model represents a lightweight yet powerful approach to generating text embeddings across multiple languages.
Implementation Details
The model utilizes a compact architecture with 6 transformer layers and a hidden size of 384 dimensions, making it efficient for production deployments while maintaining strong performance. It's built on the MiniLMv2 architecture, which is known for its effective knowledge distillation approach.
- Transformer-based architecture with 6 layers
- 384-dimensional hidden states for dense representation
- Optimized for cross-lingual semantic similarity tasks
- Efficient model size for practical applications
Core Capabilities
- Multilingual text embedding generation
- Cross-lingual information retrieval
- Semantic search across different languages
- Document similarity comparison
- Efficient text representation for downstream tasks
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its efficient multilingual capabilities while maintaining a relatively small model size. The L6-H384 architecture provides a good balance between performance and computational requirements, making it particularly suitable for production environments where resource efficiency is crucial.
Q: What are the recommended use cases?
The model is particularly well-suited for: multilingual search systems, cross-lingual document retrieval, semantic similarity matching across languages, and building efficient multilingual information retrieval systems. It's ideal for applications where you need to compare or search text across different languages efficiently.
