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.
In the Foundation models & chat space, Paraphrase Albert Small takes a focused approach. It focuses on creating dense vector representations of sentences for similarity and retrieval tasks. Paraphrase Albert Small is an open-source project aimed at developers. The project is open source (Open Source). Paraphrase Albert Small is available on the web, the command line, and API.
sentence-transformers builds and maintains Paraphrase Albert Small, and the product first shipped in 2022.
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