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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8be34a208bfa7895217a7b953823981a362e1297cc3a642dd93e0aa747b8936c
- Size of remote file:
- 4.09 kB
- SHA256:
- be0c267b3047bda19af0ece01ba8c89da10515f1324f1e95b5223509a742c2a0
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