Instructions to use SupremoUGH/image-classification-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SupremoUGH/image-classification-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="SupremoUGH/image-classification-model") 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("SupremoUGH/image-classification-model") model = AutoModelForImageClassification.from_pretrained("SupremoUGH/image-classification-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9ec95201099ef401c6ac98aaa924f82f506780905c089e3dcfc6e6166745f78e
- Size of remote file:
- 343 MB
- SHA256:
- 02e9496d47c1edd9c65ffbb29c62f2238aa998d10c73ef901252524d5f619d7c
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