Instructions to use galthran/segformer-facade with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use galthran/segformer-facade with Transformers:
# Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("galthran/segformer-facade") model = SegformerForSemanticSegmentation.from_pretrained("galthran/segformer-facade", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 532bd7892d404ba36485f8f746cdf1f13db1b426f983b7048c693b39dca71abc
- Size of remote file:
- 189 MB
- SHA256:
- 856c5309063362ee0729503113c384c0e6f35ce6ebc798980a2e2e980c1d7ad1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.