Instructions to use hf-internal-testing/tiny-random-Swinv2Backbone with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Swinv2Backbone with Transformers:
# Load model directly from transformers import AutoImageProcessor, Swinv2Backbone processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-Swinv2Backbone") model = Swinv2Backbone.from_pretrained("hf-internal-testing/tiny-random-Swinv2Backbone", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3819a3fe3ecd584d1f9f59848b40c0c23e36b692081fb07d37317cc148e3b2d8
- Size of remote file:
- 308 kB
- SHA256:
- 57ebc76a1f2a8c95b1b97ff9c6c4a2df4252e2774bcdd3997646a682ac6f24e8
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