Sentence-Transformers
A Python library for creating sentence, text, and image embeddings, enabling the conversion of text into high-dimensional numerical vectors that capture semantic meaning. It is essential for tasks like semantic search and Retrieval Augmented Generation (RAG), which often leverage vector databases.
About this tool
About
Sentence-Transformers is a Python library for creating state-of-the-art sentence, text, and image embeddings. It enables the conversion of text into high-dimensional numerical vectors that capture semantic meaning, which is essential for tasks like semantic search and Retrieval Augmented Generation (RAG), often leveraging vector databases.
Features
- Sentence, Text, and Image Embedding Creation: Generates high-dimensional numerical vectors from various data types.
- Semantic Meaning Capture: Embeddings are designed to accurately represent the semantic content of the input.
- Support for Semantic Search: Facilitates the development of systems capable of identifying semantically similar information.
- Integration with RAG: A key component for building Retrieval Augmented Generation systems.
- Python Library: Provides a convenient and accessible interface for Python developers.
License
This project is open-source and distributed under a defined license, as indicated by the presence of a LICENSE file within its repository.