This is a small ALBERT-based model from the sentence-transformers library, fine-tuned to produce semantically meaningful sentence embeddings. It is particularly effective for paraphrase identification, semantic textual similarity, and clustering. The model is lightweight and suitable for production use in search, recommendation, and RAG systems.
Paraphrase Albert Small is an Embeddings & retrieval project. It focuses on creating dense vector representations of sentences for similarity and retrieval tasks. It is built as an open-source project for developers. The project is open source (Open Source). Paraphrase Albert Small is available on the web, the command line, and API.
It is developed by sentence-transformers, and it first shipped in 2022.
Summary written by a language model from the project’s public pages.
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