Instructions to use ranwakhaled/gemma-vl-exp1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ranwakhaled/gemma-vl-exp1 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ranwakhaled/gemma-vl-exp1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5a1c1d2b150cefba314452dc53ca0df31b0ab5c47fc30c750c83d2a1bf1868bd
- Size of remote file:
- 33.4 MB
- SHA256:
- 7fad9b5f6f930b43d292eb3c56c176a69292850ddd0abc02d9ea1dac3292c87a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.