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:
- db8510ff0aea6fb1bddbb5e24aed257ab529aaa82ffe689cdd9f4b189f3f3094
- Size of remote file:
- 45.8 MB
- SHA256:
- a27b94c9f02c21c292377ab2c58a209d987bf31df3dcb77271c8788d1f76e8a7
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