Instructions to use NeuronZero/CXR-Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NeuronZero/CXR-Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="NeuronZero/CXR-Classifier") 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("NeuronZero/CXR-Classifier") model = AutoModelForImageClassification.from_pretrained("NeuronZero/CXR-Classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c15c9ff87ca0a9ec19966a7c4fd0e5e1d49f62a649b99c53ee5b1f4107d30372
- Size of remote file:
- 343 MB
- SHA256:
- 80584abcc67d75cd6b1bb645f5ea036d18ddcdef533578238eb8283f6cfc5f15
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