Instructions to use hf-internal-testing/tiny-random-DonutSwinModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-DonutSwinModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-DonutSwinModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-DonutSwinModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-DonutSwinModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 218387383f560d3f9a6280fcf2c402c01191a4603950b13c5dc5bae795a88fd2
- Size of remote file:
- 282 kB
- SHA256:
- 790701996586fe680d8523fc5ec7c2d29e409a242bb0cf16cc2cd5257a0e2e31
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