Image Classification
Transformers
PyTorch
TensorBoard
English
van
Generated from Trainer
Eval Results (legacy)
Instructions to use DunnBC22/van-base-Brain_Tumors_Image_Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DunnBC22/van-base-Brain_Tumors_Image_Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="DunnBC22/van-base-Brain_Tumors_Image_Classification") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModelForImageClassification model = AutoModelForImageClassification.from_pretrained("DunnBC22/van-base-Brain_Tumors_Image_Classification", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c6f0fede8b23a5ea702ddaed883791f54776a19b99e2eb1a3a5ba9a381f05002
- Size of remote file:
- 3.64 kB
- SHA256:
- f2682c14d0ddc15e5f41fdfa0118ebc679c72e1279a308399bf7ec6e139b3467
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