Instructions to use hf-tiny-model-private/tiny-random-ConvNextV2Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-ConvNextV2Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="hf-tiny-model-private/tiny-random-ConvNextV2Model")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-ConvNextV2Model") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-ConvNextV2Model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c605eb80abcb9fc3bdd05535fa3bec130f2bc6f1f0cbbf8f03ad6e0a57d5f721
- Size of remote file:
- 327 kB
- SHA256:
- ca8d9b1284837db32b2861a7374bd3b05c2cd3dfd5461b212168b087555a14b5
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