Instructions to use Blaise-MR/diseaseClassifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Blaise-MR/diseaseClassifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Blaise-MR/diseaseClassifier") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("Blaise-MR/diseaseClassifier") model = AutoModelForImageClassification.from_pretrained("Blaise-MR/diseaseClassifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Blaise-MR/diseaseClassifier: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/Blaise-MR/diseaseClassifier/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Blaise-MR/diseaseClassifier/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Blaise-MR/diseaseClassifier/resolve/main/pytorch_model.bin
343 MB
- Xet hash:
- f3143c487aa29c72a208c773bab1e79ae8e1a6b2ec7d92dad0677d1d03320971
- Size of remote file:
- 343 MB
- SHA256:
- 79bdb480c7c1d7418c91ca5a687005204e618a2ff6bef858f3965ef168037c79
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