Instructions to use hf-tiny-model-private/tiny-random-Mask2FormerModel 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-Mask2FormerModel 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-Mask2FormerModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-Mask2FormerModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-Mask2FormerModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 28030b6b54d463f13ebcba0b02ffc1dd26cb6bf0a5b9f1a7fecff653f470861f
- Size of remote file:
- 47.4 MB
- SHA256:
- 95a58492438340fbabce3eba282bc799055f7da9cb13ec9908d0be6f1211f18a
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