Instructions to use hf-internal-testing/tiny-random-ConvNextModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ConvNextModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="hf-internal-testing/tiny-random-ConvNextModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-ConvNextModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-ConvNextModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dea6acf1e47a777eaaa1fa80007ee52b573cdd7bc4cdcc62ef3d363dca0776dc
- Size of remote file:
- 320 kB
- SHA256:
- 72fe746a8741d22cb4699df44f68c9cae345c3ada47127d76fedbb8eeebce0a4
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