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:
- f0b420e81e63abd8bd2eb89910b3d8848284da4706b16bd03e6129b236b5346c
- Size of remote file:
- 327 kB
- SHA256:
- d1f3a76a3fe8685f41a8ab81bbcb6790b2517491a1bc8db8305f1b13165a00ee
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