Instructions to use HorcruxNo13/swinv2-tiny-patch4-window8-256 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HorcruxNo13/swinv2-tiny-patch4-window8-256 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="HorcruxNo13/swinv2-tiny-patch4-window8-256") 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("HorcruxNo13/swinv2-tiny-patch4-window8-256") model = AutoModelForImageClassification.from_pretrained("HorcruxNo13/swinv2-tiny-patch4-window8-256") - Notebooks
- Google Colab
- Kaggle
File size: 205 Bytes
71b7ad3 | 1 2 3 4 5 6 7 8 | {
"epoch": 3.0,
"total_flos": 1.00318990565376e+17,
"train_loss": 2.710611641407013,
"train_runtime": 107.4175,
"train_samples_per_second": 27.928,
"train_steps_per_second": 0.223
} |