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:
- caa707cb89a5bf160a342eec7c0aeefa108ebd2d61a1443a68448d664e55a1c6
- Size of remote file:
- 291 kB
- SHA256:
- 3fc16f1546dca713fb2bc1e3ef8619871a0e909026d08e112609491817383f4a
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