# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("darklorddad/Model-SwinV2-Large-89")
model = AutoModelForImageClassification.from_pretrained("darklorddad/Model-SwinV2-Large-89")Quick Links
Model Trained Using AutoTrain
- Problem type: Image Classification
Validation Metrics
loss: 0.37125059962272644
f1_macro: 0.8875326968782852
f1_micro: 0.8918032786885246
f1_weighted: 0.889380159243949
precision_macro: 0.9082038517038518
precision_micro: 0.8918032786885246
precision_weighted: 0.9081954816585965
recall_macro: 0.8885952380952381
recall_micro: 0.8918032786885246
recall_weighted: 0.8918032786885246
accuracy: 0.8918032786885246
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="darklorddad/Model-SwinV2-Large-89") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")