Instructions to use google/gemma-4-E4B-it with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/gemma-4-E4B-it with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("google/gemma-4-E4B-it") model = AutoModelForMultimodalLM.from_pretrained("google/gemma-4-E4B-it", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- AMD Developer Cloud
LFM3 Omni absolutely destroys every multimodal capability of this BTW
#56
by DiffusionFanatic1 - opened
Like it's not remotely close in practice, at all. The E2B next time needs to be like twice as good as this model was to even compete at all
Hi @DiffusionFanatic1 ,
Thanks for addressing the issue. Could you please share specific examples, prompts, or test cases where you noticed the difference, along with your environment details.
Like it's not remotely close in practice, at all. The E2B next time needs to be like twice as good as this model was to even compete at all
this is a 7 month old model tho and it wasn't the best vision model when it came out anyway