Instructions to use hf-tiny-model-private/tiny-random-ViTMSNModel 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-ViTMSNModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="hf-tiny-model-private/tiny-random-ViTMSNModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-ViTMSNModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-ViTMSNModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5a8b11b1c50b76c25004cdacfd170395d5b6a4e0b986a6a5f5ab5d006c2a8715
- Size of remote file:
- 176 kB
- SHA256:
- 343a3c7ac90cd53f2c22a8a7bab9709b5871a57922e0fe5ef66bd0247767cd80
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