Image Classification
Transformers
TensorBoard
Safetensors
swinv2
Generated from Trainer
Eval Results (legacy)
Instructions to use Augusto777/swinv2-tiny-patch4-window8-256-RD-FIX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Augusto777/swinv2-tiny-patch4-window8-256-RD-FIX with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Augusto777/swinv2-tiny-patch4-window8-256-RD-FIX") 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("Augusto777/swinv2-tiny-patch4-window8-256-RD-FIX") model = AutoModelForImageClassification.from_pretrained("Augusto777/swinv2-tiny-patch4-window8-256-RD-FIX", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ff0dd08a7f514a3286a9e2f2b5e34d02dcdd66f7f772ccda1315eab43b8e77a2
- Size of remote file:
- 5.37 kB
- SHA256:
- bdda2218fc23763c52a839b0c0d3456a579624f1dc075665041c7527aa8ac258
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