Instructions to use Hemg/Brain-Tumor-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hemg/Brain-Tumor-Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Hemg/Brain-Tumor-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("Hemg/Brain-Tumor-Classification") model = AutoModelForImageClassification.from_pretrained("Hemg/Brain-Tumor-Classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b9e9ce5128d5e421cf77852cf211bb5404109a858bd9838142d618e218cefea2
- Size of remote file:
- 4.92 kB
- SHA256:
- b0387d6fdefac581146a46fc3993f1b29959e150329308ab065a0b697676c4a9
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