Sentence Transformers

Sentence Transformers

Empowering Semantic Understanding

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Sentence Transformers is a Python module that provides access to state-of-the-art embedding and reranker models. It allows users to compute embeddings, calculate similarity scores, and generate sparse embeddings for various applications such as semantic search, semantic textual similarity, and paraphrase mining. The module offers a wide selection of pre-trained models and enables users to train or finetune their own models for specific use cases.

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Features

Advantages

  • Wide range of applications including semantic search and textual similarity
  • Access to a variety of pre-trained models for immediate use
  • Ability to train or finetune custom models for specific use cases
  • Efficient computation of embeddings and similarity scores
  • Supported by UKPLab and maintained by Hugging Face

Disadvantages

  • Requires Python 3.9+ and PyTorch 1.11.0+ for installation
  • Complexity in training custom models for beginners
  • Limited documentation for advanced usage scenarios

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