Instructions to use hf-internal-testing/tiny-random-BitBackbone with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-BitBackbone with Transformers:
# Load model directly from transformers import AutoImageProcessor, BitBackbone processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-BitBackbone") model = BitBackbone.from_pretrained("hf-internal-testing/tiny-random-BitBackbone") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3ec5230b8a1cbf3b28dff2da9cf1c2c692aa6d1461a949d3c2d0f0f0974ddc18
- Size of remote file:
- 89.6 kB
- SHA256:
- 6e150601f330196d66f46d5a74b2b8fb57425f8620a691b3e3ba04be73c37f9c
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