Instructions to use hf-tiny-model-private/tiny-random-DeiTModel 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-DeiTModel 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-DeiTModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-DeiTModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-DeiTModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9cb917dc9857197f0bf565ba69d1561fba3e4fb87adb1afd82ffa3f6e2b2724f
- Size of remote file:
- 199 kB
- SHA256:
- 00a015ea1a8a6b1def3fd5308e7997f83b8f05df24343dc03abf85660bc83bc2
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