Google DeepMind משחרר EmbeddingGemma 2

תקציר מקורי באנגליתGoogle DeepMind has released EmbeddingGemma 2 , an open model that embeds text, code, images, video and audio into one 768-dimensional space. It has 740M parameters, an 8K token context window and an Apache 2.0 license. It targets on-device search, classification and privacy-first RAG. This article analyzes, compares and showcase how EmbeddingGemma 2 fits in the space. Deployable today? Yes. Weights are live on Hugging Face and Kaggle , with Ollama , llama.cpp GGUF and LiteRT builds available now. What an Embedding Model Does An embedding model converts content into a vector of numbers that captures meaning. Similar items land close together, so they are easy to search and compare. In a RAG pipeline, these vectors let an LLM retrieve fresh information it was not trained on. Generating embe