Instructions to use hf-tiny-model-private/tiny-random-MobileNetV1Model 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-MobileNetV1Model 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-MobileNetV1Model")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-MobileNetV1Model") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-MobileNetV1Model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7ffb14b016c870f3c901267eff3b2bf6996b29685fb7585a86a023c15b801d39
- Size of remote file:
- 890 kB
- SHA256:
- 4487a657451d3fb3790cb183f4246e93a9ad84064d709e86bdb2a457b1841fae
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