Instructions to use Fu-chiang/bit-50-Glaucoma with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Fu-chiang/bit-50-Glaucoma with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Fu-chiang/bit-50-Glaucoma") 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("Fu-chiang/bit-50-Glaucoma") model = AutoModelForImageClassification.from_pretrained("Fu-chiang/bit-50-Glaucoma", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dbf4a8e25491f1dc712c4decae4b44b5f6ac1461f923566b93971478546d1b97
- Size of remote file:
- 94.1 MB
- SHA256:
- 540bd946cbf8df39e5d8716dbb3953e50c0f14956c8db0ac7c0223dab7585df1
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