Instructions to use dima806/gemstones_image_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dima806/gemstones_image_detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="dima806/gemstones_image_detection") 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("dima806/gemstones_image_detection") model = AutoModelForImageClassification.from_pretrained("dima806/gemstones_image_detection") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b3e37897a808700c9ce8ce2c4e69c7b253b28e40c7469e0e398bd92cbd611760
- Size of remote file:
- 344 MB
- SHA256:
- 36455f7ee256b14786d8c5ef5b69b1474d330c447b37edeab84155e8b22d913f
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