Transformers 5.19.0 adds the EmbeddingGemma2 multimodal embedding model

On October 6, 2026 Hugging Face published version 5.19.0 of its Transformers library on GitHub. The release notes add support for EmbeddingGemma2, which the notes describe as a multimodal embedding model from Google built on the Gemma 4 architecture that encodes text, images, audio, and video into a shared 768-dimensional vector space and uses Matryoshka Representation Learning so embeddings can be truncated to 512, 256, or 128 dimensions. The notes also list breaking changes: every mixture-of-experts model that computes router logits now returns them when `output_router_logits=True`, the `"paged|"` prefix for SDPA and flash attention implementations is deprecated in favor of continuous batching on the regular functions, and `Owlv2ForObjectDetection.embed_image_query` now selects the query box by objectness score. EmbeddingGemma2 itself is a Google model and is not a separate catalog entry; USASI has not tested these changes.1