Instructions to use sungile/custom-object-test4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sungile/custom-object-test4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="sungile/custom-object-test4")# Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("sungile/custom-object-test4") model = SegformerForSemanticSegmentation.from_pretrained("sungile/custom-object-test4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0ad2afcbe2c1b03f002100dc67642e829d203547fdc863d8ba7204297f3c1d2a
- Size of remote file:
- 5.3 kB
- SHA256:
- e344da738e2b83ca29b76a1aa4df1dfaffea0e4649cb3dc7152fd1e96f671004
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