# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("darklorddad/Model-SwinV2-Tiny-83")
model = AutoModelForImageClassification.from_pretrained("darklorddad/Model-SwinV2-Tiny-83")Quick Links
Model Trained Using AutoTrain
- Problem type: Image Classification
Validation Metrics
loss: 0.5218645334243774
f1_macro: 0.8312956210456212
f1_micro: 0.8377049180327869
f1_weighted: 0.8337990174670502
precision_macro: 0.8636145382395383
precision_micro: 0.8377049180327869
precision_weighted: 0.8647297329264542
recall_macro: 0.8355833333333333
recall_micro: 0.8377049180327869
recall_weighted: 0.8377049180327869
accuracy: 0.8377049180327869
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Model tree for darklorddad/Model-SwinV2-Tiny-83
Base model
microsoft/swinv2-tiny-patch4-window16-256
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="darklorddad/Model-SwinV2-Tiny-83") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")