Getting to know Google Gemma

Google Gemma is a family of lightweight, state-of-the-art open models built from the same research and technology used to create the Gemini models. These models are designed for various text generation tasks, including question answering, summarization, and reasoning.

Google Gemma is a family of lightweight, state-of-the-art open models developed by Google DeepMind and other teams across Google. The name “Gemma” is derived from the Latin word “gemma,” meaning “precious stone.” These models are designed to support innovation, collaboration, and the responsible use of artificial intelligence (AI) by providing developers with the tools to customize and deploy them in various applications and on different hardware, including mobile devices and hosted services.

The Gemma models draw inspiration and technological lineage from the Gemini family of models and are intended for the AI development community to extend and further develop. They can be used for text generation and can be customized using tuning techniques to specialize in performing specific tasks, providing more targeted and efficient generative AI solutions.

Gemma models are available in different sizes, such as 2B and 7B, and can be fine-tuned for specific tasks. They are pre-trained on a diverse dataset of web documents, code, and mathematical text, ensuring a broad range of linguistic styles, topics, and vocabulary.

Google has made Gemma accessible through several platforms, including Colab and Kaggle notebooks, and has integrated it with popular tools such as Hugging Face, MaxText, NVIDIA NeMo, and TensorRT-LLM. Gemma has set new benchmarks, outperforming other models in its size categories, igniting enthusiasm in the AI community.

They are designed with responsible AI development in mind, incorporating comprehensive safety measures to ensure safe and responsible AI development. Gemma models are optimized for Google Cloud, allowing users to deeply customize the model to their specific needs with Vertex AI’s fully-managed tools or GKE’s self-managed option. Google Cloud provides up to $500k in credits for TPU and GPU usage costs associated with research, aiming to advance research and contribute to the scientific community.

Introduction to Google Gemma

Run Google Gemma 2B and 7B on your computer for free (CPU and GPU)
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