Image Classification
Transformers
PyTorch
TensorBoard
swin
Generated from Trainer
Eval Results (legacy)
Instructions to use Devarshi/Brain_Tumor_Classification_using_swin with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Devarshi/Brain_Tumor_Classification_using_swin with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Devarshi/Brain_Tumor_Classification_using_swin") 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("Devarshi/Brain_Tumor_Classification_using_swin") model = AutoModelForImageClassification.from_pretrained("Devarshi/Brain_Tumor_Classification_using_swin", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 207 Bytes
bdbd32e | 1 2 3 4 5 6 7 8 | {
"epoch": 3.0,
"total_flos": 5.409667845997019e+18,
"train_loss": 0.15731672859854168,
"train_runtime": 52202.335,
"train_samples_per_second": 1.323,
"train_steps_per_second": 0.01
} |