Instructions to use hf-internal-testing/tiny-random-ViTModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ViTModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="hf-internal-testing/tiny-random-ViTModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-ViTModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-ViTModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 01be9fa673b712de5a2fd2d31b6a2f3bb45c58daaa82c806eb984529ea8a3a92
- Size of remote file:
- 180 kB
- SHA256:
- be3eee1acf535792fd874c30fa9eccdad214e244be11e8e52d18c6a7ad99df69
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