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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 3.0, | |
| "train_loss": 0.11622388989285186, | |
| "train_runtime": 6860.1206, | |
| "train_samples_per_second": 1.255, | |
| "train_steps_per_second": 0.079 | |
| } |