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:
- 8a49fe6ed79f20743f3f629c8ec5fd150494d82f467b0dbf4f0461d8837e1fe7
- Size of remote file:
- 4.03 kB
- SHA256:
- 9e6f3f627163db460c488c5fb2a83954e05736be334d953dc3d4ac3c0a8089d9
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