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:
- 34ce2c53103cf1c2f24e29c2e8faa53b859d574bded4958bd5b9069cc16af9f0
- Size of remote file:
- 109 MB
- SHA256:
- 60548cd844a3080037a49ac69dd619ae1447947c2652f5c19f6f613c26e33c6f
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