Instructions to use RickyIG/image_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RickyIG/image_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="RickyIG/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("RickyIG/image_classification") model = AutoModelForImageClassification.from_pretrained("RickyIG/image_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 47bb96d23b2f0f227ca97b594b07dce671963186741d6a23580ce5bb86fef437
- Size of remote file:
- 344 MB
- SHA256:
- 70b479bf7a633960ddbfef8d4385af585507892f1741626d14c4538c9d7e6a27
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