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:
- 0f346c1b5c83ccdce84f1d688e9c734b57fddc706cdae04131b75a5dd50d4c52
- Size of remote file:
- 4.03 kB
- SHA256:
- 0faceee1aac941955a754b0a0063edef451ffb4a87da35fc9c7c2b677b465ae5
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