title | emoji | colorFrom | colorTo | sdk | app_file | pinned |
---|---|---|---|---|---|---|
Lightweight Embeddings API |
👻 / 🧬 |
purple |
indigo |
docker |
app.py |
false |
LightweightEmbeddings is a fast, free, and unlimited API service for multilingual embeddings and reranking, with support for both text and images and guaranteed uptime.
- Free and Unlimited: A completely free API service with no limits on usage, making it accessible for everyone.
- Multilingual Support: Seamlessly process text in over 100+ languages for global applications.
- Text and Image Embeddings: Generate high-quality embeddings from text or image-text pairs using state-of-the-art models.
- Reranking Support: Includes powerful reranking capabilities for both text and image inputs.
- Optimized for Speed: Built with lightweight transformer models and efficient backends for rapid inference, even on low-resource systems.
- Flexible Model Support: Use a range of transformer models tailored to diverse use cases:
- Text models:
snowflake-arctic-embed-l-v2.0
,bge-m3
,gte-multilingual-base
,paraphrase-multilingual-MiniLM-L12-v2
,paraphrase-multilingual-mpnet-base-v2
,multilingual-e5-small
,multilingual-e5-base
,multilingual-e5-large
. - Image model:
siglip-base-patch16-256-multilingual
- Text models:
- Production-Ready: Easily deploy anywhere with Docker for hassle-free setup.
- Interactive Playground: Test embeddings and reranking directly via a Gradio-powered interface alongside detailed REST API documentation.
- Search and Ranking: Generate embeddings for advanced similarity-based ranking in search engines.
- Recommendation Systems: Use embeddings for personalized recommendations based on user input or preferences.
- Multimodal Applications: Combine text and image embeddings to power tasks like product catalog indexing, content moderation, or multimodal retrieval.
- Language Understanding: Enable semantic text analysis, summarization, or classification in multiple languages.
git clone https://github.com/lh0x00/lightweight-embeddings.git
cd lightweight-embeddings
Make sure Docker is installed and running on your machine.
docker build -t lightweight-embeddings .
docker run -p 7860:7860 lightweight-embeddings
The API will now be accessible at http://localhost:7860
.
/v1/embeddings
: Generate text or image embeddings using the model of your choice./v1/rank
: Rank candidate inputs based on similarity to a query.
- Visit the Swagger UI for detailed, interactive documentation.
- Explore additional resources with ReDoc.
- Test text and image embedding generation in the browser with a user-friendly Gradio interface.
- Simply visit
http://localhost:7860
after starting the server to access the playground.
- Documentation: Explore full documentation
- Hugging Face Space: Try the live demo
- GitHub Repository: View source code
- Performance-Oriented: Delivers rapid results without compromising on quality, ideal for real-world deployment.
- Highly Adaptable: Works in diverse environments, from cloud clusters to local devices.
- Developer-Friendly: Intuitive API design with robust documentation and an integrated playground for experimentation.
- lamhieu / lh0x00 – Creator and Maintainer (GitHub, HuggingFace)
Contributions are welcome! Check out the contribution guidelines.
This project is licensed under the MIT License. See the LICENSE file for details.