kevaldekivadiya/textembed repository overview

⁠TextEmbed - Embedding Inference Server

TextEmbed is a high-throughput, low-latency REST API designed for serving vector embeddings. It supports a wide range of sentence-transformer models and frameworks, making it suitable for various applications in natural language processing.

⁠Features

• High Throughput & Low Latency: Designed to handle a large number of requests efficiently.
• Flexible Model Support: Works with various sentence-transformer models.
• Scalable: Easily integrates into larger systems and scales with demand.
• Batch Processing: Supports batch processing for better and faster inference.
• OpenAI Compatible REST API Endpoint: Provides an OpenAI compatible REST API endpoint. OpenAI compatible REST API endpoint

⁠Usage

To use this Docker image, simply pull it from Docker Hub and run it with your desired configuration.

docker run kevaldekivadiya/textembed:latest --help

This command will show the help message for the TextEmbed server, detailing the available options and usage.

For Example:

docker run -p 8000:8000 kevaldekivadiya/textembed:latest --models sentence-transformers/all-MiniLM-L6-v2 --port 8000

⁠Additional Links

• GitHub Repository⁠
• PyPI Package⁠
• Documentation⁠