Instructions to use raoulmago/image_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use raoulmago/image_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="raoulmago/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("raoulmago/image_classification") model = AutoModelForImageClassification.from_pretrained("raoulmago/image_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 85a93529d719bff3854919f22506d44267f116c40d2624d20fc68f8a743a7b89
- Size of remote file:
- 4.6 kB
- SHA256:
- a4c5e9a2251a7663c1847cb760a0818e1e98d6987fb1604d361a881066bedfac
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