Instructions to use cheerfun/deepix-st with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cheerfun/deepix-st with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("cheerfun/deepix-st", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 311734896c19afdfb4315e4f367414783f7414e6b24280ee29c18811648692da
- Size of remote file:
- 471 MB
- SHA256:
- 991d157e661a28127fbc1a31c7ca8ce2fb87684e9443bd737a0eb60232282c13
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.