Image Classification
Transformers
PyTorch
TensorBoard
swin
Generated from Trainer
Eval Results (legacy)
Instructions to use sasha/swin-tiny-finetuned-dogfood with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sasha/swin-tiny-finetuned-dogfood with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="sasha/swin-tiny-finetuned-dogfood") 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("sasha/swin-tiny-finetuned-dogfood") model = AutoModelForImageClassification.from_pretrained("sasha/swin-tiny-finetuned-dogfood", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 1.0, | |
| "eval_accuracy": 0.9822222222222222, | |
| "eval_loss": 0.19010965526103973, | |
| "eval_runtime": 3.4014, | |
| "eval_samples_per_second": 66.149, | |
| "eval_steps_per_second": 2.352 | |
| } |