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:
- 64d404b49d3506d085671858cc8bb6c822f346e9c9f1aa9e8ec5e16125e7dee6
- Size of remote file:
- 308 kB
- SHA256:
- d49b642ee3a65cb4b0b0e22b418e089b6d0cfdd658a2011af67eb30da5570af2
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