Google for Developers·technology
Sebastian Russo, Ivan Llanos, and Sahil Dua from Google DeepMind introduce EmbeddingGemma 2, a lightweight open model that maps text, images, video, and audio into a single unified embedding space.
At just 740 million parameters, EmbeddingGemma 2 is engineered for on-device use cases. Watch this video to discover:
*EmbeddingGemma 2’s modular architecture with optional audio and vision encoders
*Instant media search and video moment retrieval running fully offline on device
*Retrieval-augmented generation (RAG) pipelines where sensitive data never leaves the hardware
*Fine-tuning for domain-specific use cases
🔗 Resources:
Learn about the model → https://goo.gle/4hE3Lb9
Read the developer guide → https://goo.gle/4hFnyqO
Explore on-device embeddings with Google AI Edge → https://goo.gle/3VSXqS1
Download model weights from HuggingFace → https://goo.gle/4i45qbp
Get started with the Gemma Cookbook → https://goo.gle/3TCsqVO
Have questions? Drop them in the comments.
Subscribe to Google for Developers → https://goo.gle/developers
Speakers: Sebastian Russo, Ivan Llanos, Sahil Dua
Products Mentioned: Gemma, Google AI Edge
Watch video : Introducing EmbeddingGemma 2: An open model for natively multimodal embeddings