Google Releases Open-Source DiffusionGemma 26B Model
The new 26B parameter model from DeepMind uses a diffusion-based architecture, a technique more common in image generation, to produce text.
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The new 26B parameter model from DeepMind uses a diffusion-based architecture, a technique more common in image generation, to produce text.
The new 12-billion-parameter open model from DeepMind introduces a unified 'any-to-any' architecture for advanced multimodal tasks.
The new 12-billion-parameter model from Google DeepMind is designed to handle a flexible mix of data types, moving beyond traditional text and image inputs.
The new 26-billion-parameter model from DeepMind uses a mixture-of-experts design for greater efficiency and is tuned for assistant-style tasks.
The new 31-billion-parameter model is an instruction-tuned, 'any-to-any' powerhouse released under a permissive Apache 2.0 license.
The new 4-billion-parameter model is instruction-tuned for 'any-to-any' tasks, handling a flexible mix of data types.
The new compact model from DeepMind is instruction-tuned for "any-to-any" tasks, capable of processing and generating mixed data types.
The new open-source model from DeepMind uses a Mixture-of-Experts architecture to handle both text and image inputs efficiently.
The new 31-billion-parameter model is instruction-tuned and can process both text and images, marking a significant expansion for the Gemma family.
The new 2-billion-parameter model from Google DeepMind brings efficient image-and-text understanding to the open-source Gemma family.
The new 2-billion-parameter model from DeepMind can process text, vision, and audio, making it a versatile and efficient foundation for developers.
The new 4-billion-parameter vision-language model brings image and text understanding to Google's popular open-source family.
The new 4-billion parameter model from Google DeepMind is designed for versatile input and output, handling text, images, and other data types.
The new 4B-parameter model is an instruction-tuned variant of Gemma, designed specifically for high-quality multilingual translation tasks.
The new 4-billion-parameter vision-language model is specialized for tasks in radiology, pathology, and complex clinical reasoning.
The new speech recognition model from DeepMind is trained specifically on medical dictation, aiming for higher accuracy in clinical notes.
The new 270-million-parameter model from Google DeepMind is fine-tuned specifically for reliable function calling and tool use.
The new ultra-compact model from DeepMind is designed for efficient performance in resource-constrained environments like mobile and web.