Instructions to use ahmadtrg/image_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ahmadtrg/image_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ahmadtrg/image_classification") 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("ahmadtrg/image_classification") model = AutoModelForImageClassification.from_pretrained("ahmadtrg/image_classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0ac9bb715ac7e1711dc1027b70c42a8fbf0ba01c6eac9ef7c993c13d1db44349
- Size of remote file:
- 343 MB
- SHA256:
- 86c9834d7e20bebd4ee034bb4cd7ef8da79f6b51702b6c73094cecaff604b33f
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