Instructions to use hf-tiny-model-private/tiny-random-MobileNetV2Model 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-MobileNetV2Model 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-MobileNetV2Model")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-MobileNetV2Model") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-MobileNetV2Model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 811ffcf52fa9f398f8867c117c93691d7c6e2c8d85587286ddab7346ab270803
- Size of remote file:
- 1.09 MB
- SHA256:
- 904229a2a28580939036bd47b3971e854d51d53b85aa083688eec7ba05243a37
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