How Google Uses Transformers

The article discusses how to fine-tune the Gemma 3 270M model for on-device applications, enabling developers to create custom AI models without the need for expensive hardware.

The article provides an in-depth exploration of the EmbeddingGemma architecture, detailing its origins, embedding generation process, and the comprehensive training methodology.

EmbeddingGemma is an innovative open embedding model designed for on-device AI applications, featuring 308 million parameters for efficient performance.

The article introduces Gemma 3 270M, a compact AI model designed for hyper-efficient task-specific fine-tuning.

The article introduces Gemma 3n, a mobile-first architecture designed for on-device AI, highlighting its multimodal capabilities and architectural innovations.

The article discusses the new features and improvements in Gemma 3, highlighting its vision-language capabilities, architectural changes for memory efficiency, and enhanced multilingual support.

Gemma 3 is the latest version of the Gemma open-model family, boasting enhanced capabilities such as multimodality, longer context windows, and improved reasoning.

The article discusses the launch of ShieldGemma 2, a safety content classifier model built on Gemma 3, aimed at detecting harmful content in both synthetic and natural images.

PaliGemma 2 mix is an advanced vision-language model designed for multiple tasks, allowing developers to utilize a single model for various applications such as image captioning, object detection, ...

PaliGemma 2 is the latest vision-language model from Google, designed to simplify the process of building advanced AI that can interpret visual inputs.

The Web AI Summit 2024, hosted by Google on October 18, 2024, focused on client-side AI for developers, showcasing how machine learning models can operate offline in web browsers.

The article discusses the expansion of the Responsible Generative AI Toolkit, introducing new tools designed for various large language models (LLMs) like Gemma and Gemini.

The article explores the RecurrentGemma architecture, a hybrid model that combines gated linear recurrences with local sliding window attention, enhancing performance for long context prompts.

The article provides an overview of the Gemma model family architectures, detailing its lightweight, state-of-the-art open models derived from Gemini research.

This article provides a comprehensive guide on using Gemma with Ray on Vertex AI, detailing the steps to set up, fine-tune, and deploy machine learning models.

The article discusses the release of the Gemma 2 model with 27 billion parameters, highlighting its capabilities in Keras and integration with JAX for efficient model training.

The article introduces PaliGemma, an open vision-language model, along with Gemma 2, the next generation of the Gemma models, and updates to the Responsible AI Toolkit.

This article discusses how to publish Keras models on Kaggle and Hugging Face, highlighting the ease of sharing fine-tuned models with the community.

The article introduces the expansion of the Gemma family with two new models, CodeGemma and RecurrentGemma, designed specifically for developers and researchers.

The article highlights the achievements and activities of Google Machine Learning communities in the second quarter of 2023, showcasing various training campaigns, community events, and innovative ...

The article highlights the achievements of Machine Learning Google Developer Experts (GDEs) in Q2 2021, showcasing their contributions to the global ML ecosystem through various events, projects, a...