Google has announced two new large language models, Gemma 2B, and Gemma 7B, making AI helpful for everyone. Gemma, inspired by Gemini, is a lightweight platform designed with AI principles at the forefront.
It is a pre-trained, safe, and reliable model optimized to be used in environments with limited resources, like on a laptop or cloud infrastructure.
The open-source AI model can be a great tool for creating chatbots, generating content, and anything else that a language model can do.
This article includes a quick insight into Gemma and its two latest large language models, Gemma 2B and Gemma 7B.
What is Gemma?
Gemma is a family of lightweight, state-of-the-art open models built based on Gemini models.
This latest tool developed by Google DeepMind, got its name from the Latin term Gemma, meaning “precious stone.”
The Gemma pre-trained, safe, and reliable models use automated techniques to filter out certain personal information and other sensitive data from training sets.
Google says, “Accompanying our model weights, we’re also releasing tools to support developer innovation, foster collaboration, and guide the responsible use of Gemma models. Additionally, we used extensive fine-tuning and reinforcement learning from human feedback (RLHF) to align our instruction-tuned models with responsible behaviors. To understand and reduce the risk profile for Gemma models, we conducted robust evaluations, including manual red-teaming, automated adversarial testing, and assessments of model capabilities for dangerous activities. These evaluations are outlined in our model card.”
Gemma to help developers and researchers prioritize building safe and responsible AI applications. The three features under the Responsible Generative AI Toolkit available with Gemma are:
- Safety classification
- Debugging
- Guidance
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What does Gemma offer?
Gemma surpasses significantly larger models on key benchmarks while adhering to our rigorous standards for safe and responsible outputs. Google Gemma is available worldwide. Here are the key details to know:
- Google Gemma is accessible through multi-framework Keras 3.0, native PyTorch, JAX, and Hugging Face Transformers.
- Gemma models run across popular device types, including laptop, desktop, IoT, mobile, and cloud, enabling broadly accessible AI capabilities.
- Google partnered with NVIDIA to optimize Gemma for NVIDIA GPUs, from data centers to the cloud to local RTX AI PCs, ensuring industry-leading performance and integration with cutting-edge technology.
- Advanced customization is available with fully-managed Vertex AI tools or with self-managed GKE, including deployment to cost-efficient infrastructure across GPU, TPU, and CPU from either platform.
Also Read: Google AI chatbot ‘Bard’ will soon be called as ‘Gemini’
About Gemma 2B and 7B
Google recently launched the Gemma 2B and 7B to achieve best-in-class performance for their sizes compared to other open models. Gemma models are capable of running directly on a developer laptop or desktop computer. Notably, Gemma surpasses significantly larger models on key benchmarks while adhering to our rigorous standards for safe and responsible outputs.
- Ready-to-use Colab and Kaggle notebooks, alongside integration with popular tools such as Hugging Face, MaxText, NVIDIA NeMo, and TensorRT-LLM, make it easy to get started with Gemma.
- Pre-trained and instruction-tuned Gemma models can run on your laptop, workstation, or Google Cloud with easy deployment on Vertex AI and the Google Kubernetes Engine (GKE).
- Terms of use permit responsible commercial usage and distribution for all organizations, regardless of size.
In conclusion, Gemma is built for the open community of developers and researchers powering AI innovation. You can start working with Gemma today using free access to Kaggle, a free tier for Colab notebooks, and $300 in credits for first-time Google Cloud users.
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