E5_SMALL_384 is a light text embedding model for fast semantic grouping and search in EIDORA. It is described as a compact text model that runs comfortably on ordinary laptops, and it is identified as a feature extraction model for text. The page also lists it with ONNX, onnxruntime, embeddings, and text-related tags.
Its stated uses are fast first-pass grouping of text notes, captions, and metadata, along with semantic search over medium and large text projects on laptops. It is also called a compact starter model for EIDORA text embedding workflows. The same page marks it as not ideal for long-document reasoning or generation, fine-grained domain retrieval where a larger text embedding model is acceptable, or image, video, or audio inputs. The compute tier is listed as light, with small download size, low memory use, and faster CPU runtime.
E5_SMALL_384 is available under the MIT license. It is hosted on Hugging Face under the EIDORA organization, and the page references EIDORA and EIDORA model-zoo context. Its arXiv reference is 2212.03533.
E5 Small 384 is an Embeddings & retrieval project. It focuses on providing a lightweight, open-source model for fast semantic grouping and search of text data. It is built as an open-source project for AI researchers and developers. The project is open source (MIT). E5 Small 384 is available on the web, the command line, and API, and it can be self-hosted.
EIDORA builds and maintains E5 Small 384, and it first shipped in 2019. The project is developed in the open on GitHub with 22.2k stars. Among its 5 catalogued features are text embedding, semantic search, and fast inference.
Summary written by a language model from the project’s public pages.
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