Instructions to use hf-tiny-model-private/tiny-random-ConvNextBackbone 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-ConvNextBackbone with Transformers:
# Load model directly from transformers import AutoImageProcessor, ConvNextBackbone processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-ConvNextBackbone") model = ConvNextBackbone.from_pretrained("hf-tiny-model-private/tiny-random-ConvNextBackbone", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0462e8807295f54ec6f61341526a68fdefbfc10ed073ab38f5c01baeb5dbd4c5
- Size of remote file:
- 339 kB
- SHA256:
- 34fafedc4bf6f3a5482e4c327412a11d14e0e607849e9aa649c150df78f8513b
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