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
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:b20e63e2e5c26326bfb17299f18186c64406b317cc0f4d87067d1c7c8e3b2227
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size 108739372
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