Instructions to use cominder/Iwin-Transformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cominder/Iwin-Transformer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="cominder/Iwin-Transformer")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("cominder/Iwin-Transformer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c869847e410094e2fbc092cb41bebc190ec9b7ab194888229c60ef66527dbc4d
- Size of remote file:
- 206 MB
- SHA256:
- 08a95b3ccf3f2edb8f82b4f0672d88f334f810fe33cdedc1780cc49b09ebdd08
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.