Instructions to use anum231/cancer_classifier_100 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anum231/cancer_classifier_100 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="anum231/cancer_classifier_100") 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("anum231/cancer_classifier_100") model = AutoModelForImageClassification.from_pretrained("anum231/cancer_classifier_100", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f21a107b9bb2212082a992916ed6fd088ec2a3ecbd971fd5bb53717daf14d654
- Size of remote file:
- 686 MB
- SHA256:
- 13e7bcafb814d5c7e0d1bf4a67cc63aeda1cfcfe46b12886fd1a085e60005eb5
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