Instructions to use hf-internal-testing/tiny-random-ResNetBackbone with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ResNetBackbone with Transformers:
# Load model directly from transformers import AutoImageProcessor, ResNetBackbone processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-ResNetBackbone") model = ResNetBackbone.from_pretrained("hf-internal-testing/tiny-random-ResNetBackbone", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2346f247190121ffcb994237c46a3d709e3ec2e8a7a87b4fc5873cbdf7669bd4
- Size of remote file:
- 106 kB
- SHA256:
- 9004f7cfed315553495d7d894a2e0389b2faa6f502a005ee0a421ad7250e2e62
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