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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4372aec79021849a22fe49a2a1cf62fe82dac2a61c40694d0b6f91de97e468be
- Size of remote file:
- 437 kB
- SHA256:
- 35debcee90327f19de1405594ef2a7f2fe7dc9e51847b6308c4afcc5d998a4b1
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