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
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pipeline_tag: image-classification
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datasets:
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- imagenet-1k
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library_name: pytorch
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---
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This is a EfficientNetB0 model, trained on the ImageNet1k Dataset.
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pipeline_tag: image-classification
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datasets:
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- imagenet-1k
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---
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This is a EfficientNetB0 model, trained on the ImageNet1k Dataset.
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