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:
- 7ff2d913b616a2708da98349f4dfdffd4d49f3a8497babb5faa4a2a907824eeb
- Size of remote file:
- 180 kB
- SHA256:
- a2a803f5834a487310fedd47ad457cc26adb67d4fbeb602bb8afc2579943bd30
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