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:
- 24339ba1984ad39b3702f72464ede414ee88758925149d61c8fd64abe6a6090c
- Size of remote file:
- 188 MB
- SHA256:
- caa6a00ab903d697709af2442e051d8636ccdf44c907569aaad3e640d96f322a
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