Instructions to use zuppif/resnet-d-152 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zuppif/resnet-d-152 with Transformers:
# Load model directly from transformers import ResNetDForImageClassification model = ResNetDForImageClassification.from_pretrained("zuppif/resnet-d-152", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8bc84a481b0c5af6822d990a95240a132bb38596c71ba3bca1708914fb7b72ef
- Size of remote file:
- 242 MB
- SHA256:
- 471ddde52b96a8580ec9ca29778211c73729b4c5b433df860e7982f275b950d1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.