Instructions to use asajjad/lung_ct_covid_binary_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use asajjad/lung_ct_covid_binary_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="asajjad/lung_ct_covid_binary_classification") 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("asajjad/lung_ct_covid_binary_classification") model = AutoModelForImageClassification.from_pretrained("asajjad/lung_ct_covid_binary_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0b20982e31ee67a6eb0287dc89616a821dc342f3870c00db8badbe249354a242
- Size of remote file:
- 4.92 kB
- SHA256:
- 11793bd7faf5eb060a11817f9bce30b7501250fa348291da16d0149108c59e23
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