Instructions to use maazie/EfficientNetB0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use maazie/EfficientNetB0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="maazie/EfficientNetB0") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("maazie/EfficientNetB0") model = AutoModelForImageClassification.from_pretrained("maazie/EfficientNetB0") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7c952499ad3f25b0a03ef8384b47ccc6b9d8648a1df4866abea232c8a4c6e2d8
- Size of remote file:
- 21.5 MB
- SHA256:
- 418561d4cb83b22190157cbe49cb08502691d259617a4253322f33742a9fb54d
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