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:
- e0ed1a33f0e15376b378bd06bddc2b16302f1d4a824f0f84a4d1ae43dab29d7c
- Size of remote file:
- 437 kB
- SHA256:
- f63b01d7504df3b2c234139fade33d7e4ddcdadf62c85e5afe50920393eb8790
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