Instructions to use hf-internal-testing/tiny-random-DeiTModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-DeiTModel 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-DeiTModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-DeiTModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-DeiTModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 24de887b5590be2686d0aa2f4ed4ab7986197a803c07d9a73adcb674b2540a01
- Size of remote file:
- 292 kB
- SHA256:
- 824ddb691744adc7cf455c5aa324fa2ac687f1a0918a4d8ac016942c85437c45
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