Instructions to use hf-internal-testing/tiny-random-DetrForSegmentation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-DetrForSegmentation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="hf-internal-testing/tiny-random-DetrForSegmentation")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageSegmentation processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-DetrForSegmentation") model = AutoModelForImageSegmentation.from_pretrained("hf-internal-testing/tiny-random-DetrForSegmentation") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 30e956ffea7749b88a162a140f8530f0e3e272cdd0111399d19a75ed261ac2dc
- Size of remote file:
- 109 MB
- SHA256:
- b20e63e2e5c26326bfb17299f18186c64406b317cc0f4d87067d1c7c8e3b2227
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