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:
- 90f9c38ccbdcc41defeed7b0801b97d8050bb5a507a2663e8d7c35bc05289524
- Size of remote file:
- 327 kB
- SHA256:
- acfda1d57ba8ddb392f6cf241d7343213065a30c5fc4bbf243c2be001f30867f
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