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
Download train_results.json from dvs/swin-tiny-patch4-window7-224-uploads-classifier-v2: direct link, hf CLI and curl.
- Browser
- Download file 210 Bytes
-
https://huggingface.co/dvs/swin-tiny-patch4-window7-224-uploads-classifier-v2/resolve/main/train_results.json
- Command line
-
hf download hf://dvs/swin-tiny-patch4-window7-224-uploads-classifier-v2/train_results.json
-
curl -L -o train_results.json https://huggingface.co/dvs/swin-tiny-patch4-window7-224-uploads-classifier-v2/resolve/main/train_results.json
210 Bytes
| { | |
| "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 | |
| } |