Gemma 2

What is Gemma 2?

Gemma 2 is a newly released model that offers three powerful and efficient versions with parameter sizes of 2, 9, and 27 billion. It is equipped with built-in safety advancements to enhance its performance. Gemma 2 is designed to deliver outsized performance and unmatched efficiency, focusing on achieving fast inference across various hardware configurations. This model has been optimized for rapid and reliable deployment in diverse real-world scenarios. With its redesigned architecture, Gemma 2 aims to provide blazing-fast inference capabilities, making it a valuable asset for tasks requiring high-speed processing and efficiency.

Who created Gemma 2?

Gemma 2 was created by Google. The Gemma model family includes Gemma 1 and Gemma 2, with the latter having a parameter size of 2.6 billion. Gemma 2 offers three powerful models with built-in safety advancements. Additionally, ShieldGemma, a safety content classifier, is built upon Gemma 2 to enhance user safety.

How to use Gemma 2?

To use Gemma 2 effectively, follow these steps:

1. Explore Gemma Models: Dive deep into Gemma models by accessing Weights and Biases Model Registry and Launch tools through step-by-step examples available online.

2. Visit Gemma Cookbook: Discover practical recipes and examples showcasing Gemma's power for tasks like image captioning with PaliGemma, code generation with CodeGemma, and building chatbots with fine-tuned Gemma models.

3. Utilize Google Cloud: For optimized performance, deploy Gemma 2 on Google Cloud, leveraging TPU optimization for market-leading performance and total cost of ownership on Vertex AI.

4. Experiment with Gemma Models: Adapt Gemma models to unique domains and data by leveraging different backend frameworks via platforms like Colab.

5. Benchmark Comparison:

   • Gemma 2: Handles 27B processes at 83.7 efficiency.
   • Gemma 1: Processes 2.6B tasks with 16.7 efficiency.
   • Mistral: Manages 9B tasks at 84.2 efficiency.

By following these steps, users can harness the full capabilities of Gemma 2, from exploring models to deploying them on optimized platforms like Google Cloud.