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:
- 38a3f11c93f5516c10caa670b358fed3b5b96525e67cac3d454fd6a040d5c90e
- Size of remote file:
- 437 kB
- SHA256:
- b25639790eeba1b056be69c62e334e7e6cc8364ee83a09e1da3da3c73c72364c
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