Instructions to use gitfreder/image_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gitfreder/image_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="gitfreder/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("gitfreder/image_classification") model = AutoModelForImageClassification.from_pretrained("gitfreder/image_classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- af3227363a82292ee1778eb4a742b632d2ab4ce48989e04ab3420a6a1978da57
- Size of remote file:
- 5.11 kB
- SHA256:
- 10103e98c54654c053c42f7fb607177721d4f0cf70d723fc98979551fc5630d1
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