Instructions to use hf-tiny-model-private/tiny-random-ResNetBackbone with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-ResNetBackbone with Transformers:
# Load model directly from transformers import AutoImageProcessor, ResNetBackbone processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-ResNetBackbone") model = ResNetBackbone.from_pretrained("hf-tiny-model-private/tiny-random-ResNetBackbone") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f86d2bf2e6463b16a07f0f1c41d14af3968c2f5899b7688de404b2b50acea5c1
- Size of remote file:
- 106 kB
- SHA256:
- 28fa4f812b0b717f78f689bb1c3e3d4a0160be21711475eb51af0a1ca36ca9ac
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