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:
- 13146a1697252843bd7ca467a91d4962354533558ed275ec0804be8220cdc0d8
- Size of remote file:
- 344 MB
- SHA256:
- 75b968a5900c6a62eb63ea79bdcdf5b670bfbe225e2d10d7994b360094a6f334
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