bge-m3-GGUF is a quantized text embedding model distributed in GGUF format for efficient local inference. It is designed for feature extraction and retrieval tasks, allowing users to generate embeddings without cloud dependencies. Ideal for machine learning engineers seeking open-source, local solutions.
Bge M3 sits in PulseGate's Foundation models & chat category. It focuses on enabling efficient local text embedding and retrieval without relying on cloud APIs. Bge M3 is an open-source project aimed at machine learning engineers. The project is open source (Apache-2.0). The product ships for the command line, and it can be self-hosted.
Behind Bge M3 is SmartTasks.cloud, and the product first shipped in 2022. The project is developed in the open on GitHub with 3.4k stars and 382 commits in the last 90 days. Across PulseGate's embedding index, Bge M3 has few near neighbours, marking it as relatively distinct. Among its 5 catalogued features are feature extraction, embeddings, and quantized model.
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