Image Classification
Transformers
TensorBoard
Safetensors
swin
Generated from Trainer
Eval Results (legacy)
Instructions to use djbp/swin-base-patch4-window7-224-MM_Classification_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use djbp/swin-base-patch4-window7-224-MM_Classification_base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="djbp/swin-base-patch4-window7-224-MM_Classification_base") 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-base-patch4-window7-224-MM_Classification_base") model = AutoModelForImageClassification.from_pretrained("djbp/swin-base-patch4-window7-224-MM_Classification_base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 10.0, | |
| "total_flos": 7.539281902738575e+18, | |
| "train_loss": 0.3468283264260543, | |
| "train_runtime": 12701.0006, | |
| "train_samples_per_second": 7.577, | |
| "train_steps_per_second": 0.015 | |
| } |