Google launches Gemma 2, its subsequent technology of open fashions

Constructed for builders and researchers

Gemma 2 isn’t solely extra highly effective, it is designed to extra simply combine into your workflows:

• Open and accessible: Similar to the unique Gemma fashions, Gemma 2 is offered underneath our commercially-friendly Gemma license, giving builders and researchers the flexibility to share and commercialize their improvements.
• Broad framework compatibility: Simply use Gemma 2 together with your most well-liked instruments and workflows because of its compatibility with main AI frameworks like Hugging Face Transformers, and JAX, PyTorch and TensorFlow by way of native Keras 3.0, vLLM, Gemma.cpp, Llama.cpp and Ollama. As well as, Gemma is optimized with NVIDIA TensorRT-LLM to run on NVIDIA- accelerated infrastructure or as an NVIDIA NIM inference microservice. You’ll be able to fine-tune at present with Keras and Hugging Face. We’re actively working to allow extra parameter-efficient fine-tuning choices.
• Easy deployment: Beginning subsequent month, Google Cloud clients will have the ability to simply deploy and handle Gemma 2 on Vertex AI.

Discover the brand new Gemma Cookbook, a set of sensible examples and recipes to information you thru constructing your individual purposes and fine-tuning Gemma 2 fashions for particular duties. Uncover the best way to simply use Gemma together with your tooling of alternative, together with for widespread duties like retrieval-augmented technology.

Accountable AI growth

We’re dedicated to offering builders and researchers with the assets they should construct and deploy AI responsibly, together with by our Accountable Generative AI Toolkit. The lately open-sourced LLM Comparator helps builders and researchers with in-depth analysis of language fashions. Beginning at present, you need to use the companion Python library to run comparative evaluations together with your mannequin and information, and visualize the ends in the app. Moreover, we’re actively engaged on open sourcing our textual content watermarking know-how, SynthID, for Gemma fashions.

When coaching Gemma 2, we adopted our sturdy inside security processes, filtering pre-training information and performing rigorous testing and analysis towards a complete set of metrics to establish and mitigate potential biases and dangers. We publish our outcomes on a big set of public benchmarks associated to security and representational harms.