Image Classification
Transformers
PyTorch
TensorBoard
swin
Generated from Trainer
Eval Results (legacy)
Instructions to use dvs/swin-tiny-patch4-window7-224-uploads-classifier-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dvs/swin-tiny-patch4-window7-224-uploads-classifier-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="dvs/swin-tiny-patch4-window7-224-uploads-classifier-v2") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("dvs/swin-tiny-patch4-window7-224-uploads-classifier-v2") model = AutoModelForImageClassification.from_pretrained("dvs/swin-tiny-patch4-window7-224-uploads-classifier-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 210 Bytes
f22cf1c | 1 2 3 4 5 6 7 8 | {
"epoch": 20.0,
"total_flos": 1.1677328181960376e+18,
"train_loss": 0.13230072516534064,
"train_runtime": 1894.9319,
"train_samples_per_second": 24.149,
"train_steps_per_second": 0.19
} |