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:
- ac178205651e33eedff7d9f999f8c2a0b69b97ccae95fb74ad04bfc6f33f9b53
- Size of remote file:
- 343 MB
- SHA256:
- bd81e2b49783ffc058b492d1abd30c88c21f5f1e40d168839d23e992016d4ad8
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