Instructions to use Pazel/brain-tumor-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Pazel/brain-tumor-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Pazel/brain-tumor-detection") 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("Pazel/brain-tumor-detection") model = AutoModelForImageClassification.from_pretrained("Pazel/brain-tumor-detection") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 955c8a51e043e5eecc2069bc196ee7bdaa03b2848cc7b6486d88d630ab3a23f3
- Size of remote file:
- 3.45 kB
- SHA256:
- c4ab63d5f6d0fb909fa97bcee278f362089f3d520d9f4ae886dde9f1d245b489
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