Instructions to use hf-tiny-model-private/tiny-random-MaskFormerModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-MaskFormerModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-MaskFormerModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-MaskFormerModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-MaskFormerModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 29042f5e522816dca878f80ec4573ae62ffbdfd3c0c0333eb2b34b94578076dd
- Size of remote file:
- 45.7 MB
- SHA256:
- 920ca23805003625743f1a74eb2148b7df372428e3a6f252e8b8186b70b2afe2
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