Instructions to use google/gemma-4-12B-it with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/gemma-4-12B-it with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("google/gemma-4-12B-it") model = AutoModelForImageTextToText.from_pretrained("google/gemma-4-12B-it") - Notebooks
- Google Colab
- Kaggle
Good, Google
#9
by dof-studio-org - opened
Happy to see a 12b dense model. Hope you have another bigger MoE unreleased :)
Most users like a 9b ~ 12b dense model because it can be easily fine tuned on a single node!
Happy to see a 12b dense model. Hope you have another bigger MoE unreleased :)
The MOE table is looking real empty rn with just 1 model wink wink
I will name my next child Jeffdean if we get a 124B MoE