Instructions to use hf-internal-testing/tiny-random-ConvNextV2Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ConvNextV2Model 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-ConvNextV2Model")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-ConvNextV2Model") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-ConvNextV2Model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- be5df0d8521c3b588193189545b0e53cd8c2948fc89ce26e2413514e4d32af65
- Size of remote file:
- 327 kB
- SHA256:
- 139d47501142a77377725ea3aa6fa694fd5de26d4eb370875bb0ea0428ec272f
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