Accountable by design
Gemma is designed with our AI Principles on the forefront. As a part of making Gemma pre-trained fashions protected and dependable, we used automated strategies to filter out sure private info and different delicate knowledge from coaching units. Moreover, we used intensive fine-tuning and reinforcement studying from human suggestions (RLHF) to align our instruction-tuned fashions with accountable behaviors. To know and scale back the chance profile for Gemma fashions, we carried out sturdy evaluations together with guide red-teaming, automated adversarial testing, and assessments of mannequin capabilities for harmful actions. These evaluations are outlined in our Model Card.
We’re additionally releasing a brand new Responsible Generative AI Toolkit along with Gemma to assist builders and researchers prioritize constructing protected and accountable AI functions. The toolkit contains:
- Security classification: We offer a novel methodology for constructing sturdy security classifiers with minimal examples.
- Debugging: A mannequin debugging tool helps you examine Gemma’s habits and deal with potential points.
- Steerage: You’ll be able to entry greatest practices for mannequin builders primarily based on Google’s expertise in creating and deploying massive language fashions.
Optimized throughout frameworks, instruments and {hardware}
You’ll be able to fine-tune Gemma fashions by yourself knowledge to adapt to particular utility wants, akin to summarization or retrieval-augmented era (RAG). Gemma helps all kinds of instruments and techniques:
- Multi-framework instruments: Carry your favourite framework, with reference implementations for inference and fine-tuning throughout multi-framework Keras 3.0, native PyTorch, JAX, and Hugging Face Transformers.
- Cross-device compatibility: Gemma fashions run throughout in style system varieties, together with laptop computer, desktop, IoT, cell and cloud, enabling broadly accessible AI capabilities.
- Chopping-edge {hardware} platforms: We’ve partnered with NVIDIA to optimize Gemma for NVIDIA GPUs, from knowledge middle to the cloud to native RTX AI PCs, making certain industry-leading efficiency and integration with cutting-edge expertise.
- Optimized for Google Cloud: Vertex AI gives a broad MLOps toolset with a variety of tuning choices and one-click deployment utilizing built-in inference optimizations. Superior customization is on the market with fully-managed Vertex AI instruments or with self-managed GKE, together with deployment to cost-efficient infrastructure throughout GPU, TPU, and CPU from both platform.
Free credit for analysis and improvement
Gemma is constructed for the open group of builders and researchers powering AI innovation. You can begin working with Gemma right now utilizing free entry in Kaggle, a free tier for Colab notebooks, and $300 in credit for first-time Google Cloud customers. Researchers can even apply for Google Cloud credits of as much as a collective $500,000 to speed up their tasks.
Getting began
You’ll be able to discover extra about Gemma and entry quickstart guides on ai.google.dev/gemma.
As we proceed to develop the Gemma mannequin household, we stay up for introducing new variants for various functions. Keep tuned for occasions and alternatives within the coming weeks to attach, study and construct with Gemma.
We’re excited to see what you create!
