Instructions to use oohtmeel/swin-tiny-patch4-finetuned-lung-cancer-ct-scans with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use oohtmeel/swin-tiny-patch4-finetuned-lung-cancer-ct-scans with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="oohtmeel/swin-tiny-patch4-finetuned-lung-cancer-ct-scans") 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("oohtmeel/swin-tiny-patch4-finetuned-lung-cancer-ct-scans") model = AutoModelForImageClassification.from_pretrained("oohtmeel/swin-tiny-patch4-finetuned-lung-cancer-ct-scans", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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