Instructions to use kd13/Modern-MobileNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kd13/Modern-MobileNet with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="kd13/Modern-MobileNet", trust_remote_code=True) pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModelForImageClassification model = AutoModelForImageClassification.from_pretrained("kd13/Modern-MobileNet", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6ae3d1900034edf64ca32de27dd3de2c70dfad77a64e1b0868a20a00092810af
- Size of remote file:
- 13.7 MB
- SHA256:
- 67bb70c91c77ba352b6c9f48842af3c7eb8568dae98768912dd77ae01fb6838b
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