Instructions to use jaytonde05/Kaggle_UBC_Classification_augmented with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jaytonde05/Kaggle_UBC_Classification_augmented with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="jaytonde05/Kaggle_UBC_Classification_augmented") 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("jaytonde05/Kaggle_UBC_Classification_augmented") model = AutoModelForImageClassification.from_pretrained("jaytonde05/Kaggle_UBC_Classification_augmented", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d6ac3fd172c55a182a940bca78620d8ac3ec5ae763106b381589bd8d6102162e
- Size of remote file:
- 343 MB
- SHA256:
- 146d62e42e58c23d124cbc7c994df5bb9aecf80c76d2723cce8dfaf4a088e114
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