Instructions to use sungile/custom-object-test3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sungile/custom-object-test3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="sungile/custom-object-test3")# Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("sungile/custom-object-test3") model = SegformerForSemanticSegmentation.from_pretrained("sungile/custom-object-test3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8c956a3220f7ed0d0210276836988d54cd7263db79b7b905db95c66fa02f9a1b
- Size of remote file:
- 5.3 kB
- SHA256:
- d07fb4280457b422679cf0abf5373f25e113121a24e7eae47ddfc9baa998f71e
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