Instructions to use GarayMC/cracksmcc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GarayMC/cracksmcc with Transformers:
# Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("GarayMC/cracksmcc") model = SegformerForSemanticSegmentation.from_pretrained("GarayMC/cracksmcc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 77f88d0ec8945a8f65877ff23e135795a7b13a9091f5cded9222548fc5432d8b
- Size of remote file:
- 15 MB
- SHA256:
- 65fee139ce804bfc6aed70233f54788a079e45eaaf05386f06e1eff4d577cc9d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.