Instructions to use sngsfydy/EfficientNet_with_Trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sngsfydy/EfficientNet_with_Trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="sngsfydy/EfficientNet_with_Trainer") 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("sngsfydy/EfficientNet_with_Trainer") model = AutoModelForImageClassification.from_pretrained("sngsfydy/EfficientNet_with_Trainer") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 57689e977480662597eda64709da630afd0449f736c4cade273b746485b34aab
- Size of remote file:
- 31.3 MB
- SHA256:
- cf3da156f79c229277771f6c113c9a8076ab7ff0991331d3cb60ed8a847f97df
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