Image Classification
timm
ONNX
Safetensors
mobile-screenshots
phone-screenshots
screenshot-analysis
content-safety
Instructions to use yapwithai/phone-screen-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use yapwithai/phone-screen-classifier with timm:
import timm model = timm.create_model("hf_hub:yapwithai/phone-screen-classifier", pretrained=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 63cbbde033ce0fe14447e49e91c016990a3cf57d968adf290f673e5551dedd38
- Size of remote file:
- 105 MB
- SHA256:
- 7e22dfcf02e0993c23ea02f729d62190e85ff9e8ae5cf01046c0b78942c94e09
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.