Instructions to use hf-tiny-model-private/tiny-random-DonutSwinModel 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-DonutSwinModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-DonutSwinModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-DonutSwinModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-DonutSwinModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1f6814913437656d478fbf387786f7fdf3f9d28dbb523ad9813911b48c211eb0
- Size of remote file:
- 265 kB
- SHA256:
- 6b2a93b667e8bb593c9d16fd1b529e0d889475a698a1b8b459dc697c32544b29
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