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:
- 39dcfc0ee88541ac72986844848fbaab664e7f04242901a22f71b79a0ade17fb
- Size of remote file:
- 282 kB
- SHA256:
- 324e548dfe60e03e0b75c1e3345ad589675fd5a96c151db78d21595c0a0dbc69
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