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:
- 9a73def7639737ac47229bb74e26988fcce16541b2977053a90a71eb5435aab7
- Size of remote file:
- 4.92 kB
- SHA256:
- 0fcde71267faef3288902b885e4aa4cfb36a7b0ebfeccfd0e1505e2ba3c2e468
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.