Instructions to use hf-internal-testing/tiny-random-SwinModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-SwinModel 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-SwinModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-SwinModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-SwinModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d9e103e8badbe5a0a58bfabe4eec1c886aa3f1f03bf57b9c1c6819a1a65d701e
- Size of remote file:
- 265 kB
- SHA256:
- b3082201ac0dece87dfd4bf7cab0ebc13ab6a345af76c70de40d371e95444d50
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