Image Classification
Transformers
PyTorch
TensorBoard
regnet
Generated from Trainer
Eval Results (legacy)
Instructions to use DunnBC22/regnet-y-064-Brain_Tumors_Image_Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DunnBC22/regnet-y-064-Brain_Tumors_Image_Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="DunnBC22/regnet-y-064-Brain_Tumors_Image_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("DunnBC22/regnet-y-064-Brain_Tumors_Image_Classification") model = AutoModelForImageClassification.from_pretrained("DunnBC22/regnet-y-064-Brain_Tumors_Image_Classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 241a272cfc309241101f54f29477b311a36b7c391498dcc3f9a9d55d8f490cb6
- Size of remote file:
- 3.64 kB
- SHA256:
- af4385ba10a01e1f7394d34ffa4442b810d3899987f4fc8170db21335acd5ac7
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