Instructions to use hf-internal-testing/tiny-random-MaskFormerModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MaskFormerModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-MaskFormerModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-MaskFormerModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-MaskFormerModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ae29163389088234e98b767dc1d101948429e6f1ad69ec2c71150785acb7e2cc
- Size of remote file:
- 45.7 MB
- SHA256:
- ec81d6e52fc1f23f786343645eea1940d43c3ef840382b5cd055e64dfe5782ed
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