Instructions to use Sanio7791/gemma-4-E2B-it with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sanio7791/gemma-4-E2B-it with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("Sanio7791/gemma-4-E2B-it") model = AutoModelForMultimodalLM.from_pretrained("Sanio7791/gemma-4-E2B-it") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6f118f99d2102f27139df83cbbb4966cf3ead715db89ca9fde3b36e240b3c133
- Size of remote file:
- 10.2 GB
- SHA256:
- 2db5482b20d746879bb3ef79b5203e9075a2e2b98f54ec7c2f281c1477ddc550
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.