Image Classification
Transformers
TensorBoard
Safetensors
swin
Generated from Trainer
Eval Results (legacy)
Instructions to use djbp/swin-tiny-patch4-window7-224-MM_Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use djbp/swin-tiny-patch4-window7-224-MM_Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="djbp/swin-tiny-patch4-window7-224-MM_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("djbp/swin-tiny-patch4-window7-224-MM_Classification") model = AutoModelForImageClassification.from_pretrained("djbp/swin-tiny-patch4-window7-224-MM_Classification") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 9.846153846153847, | |
| "total_flos": 2.0293244994235208e+18, | |
| "train_loss": 0.3741051137447357, | |
| "train_runtime": 7958.3559, | |
| "train_samples_per_second": 10.415, | |
| "train_steps_per_second": 0.02 | |
| } |