LABSE-Vit-L-14
| Property | Value |
|---|---|
| Author | M-CLIP |
| Model Type | Multilingual CLIP Text Encoder |
| Architecture | Vision Transformer L/14 |
| Model URL | https://huggingface.co/M-CLIP/LABSE-Vit-L-14 |
What is LABSE-Vit-L-14?
LABSE-Vit-L-14 is a powerful multilingual extension of OpenAI's CLIP model, designed to process text in multiple languages while maintaining compatibility with vision transformers. This model specifically focuses on the text encoding component, working seamlessly with the ViT-L-14 image encoder from OpenAI's CLIP.
Implementation Details
The model utilizes advanced transformer architecture and can be easily implemented using the multilingual-clip package. It requires both multilingual-clip and CLIP packages for full functionality, supporting text embedding generation across numerous languages.
- Supports multiple languages including English, German, Spanish, French, Chinese, and more
- Achieves 91.6% R@10 score for English text-to-image retrieval
- Maintains strong performance across non-English languages (80-90% R@10)
Core Capabilities
- Multilingual text encoding compatible with CLIP's vision model
- High-performance cross-lingual text-to-image retrieval
- Efficient embedding generation for 11+ languages
- Seamless integration with existing CLIP vision models
Frequently Asked Questions
Q: What makes this model unique?
The model's ability to process multiple languages while maintaining high performance levels comparable to English-only models sets it apart. It achieves impressive R@10 scores across various languages while maintaining compatibility with CLIP's vision architecture.
Q: What are the recommended use cases?
The model is ideal for multilingual text-to-image retrieval systems, cross-lingual content matching, and applications requiring multilingual understanding in visual contexts. It's particularly useful for building multilingual image search systems and cross-lingual visual understanding tasks.
