EmbeddingGemma model card Model Page : EmbeddingGemma Resources and Technical Documentation : Responsible Generative AI Toolkit EmbeddingGemma on Kaggle EmbeddingGemma on Vertex Model Garden Terms of Use : Terms Authors : Google DeepMind Model Information Description EmbeddingGemma is a 300M parameter, state of the art for its size, open embedding model from Google, built from Gemma 3 (with T5Gemma initialization) and the same research and technology used to create Gemini models. EmbeddingGemma produces vector representations of text, making it well suited for search and retrieval tasks, including classification, clustering, and semantic similarity search. This model was trained with data in 100+ spoken languages. The small size and on device focus makes it possible to deploy in environments with limited resources such as mobile phones, laptops, or desktops, democratizing access to state of the art AI models and helping foster innovation for everyone. Inputs and outputs Input: Text string, such as a question, a prompt, or a document to be embedded Maximum input context length of 2048 tokens Output: Numerical vector representations of input text data Output embedding dimension size…
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