# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("Kushagra07/autotrain-swinv2-tiny-patch4-window8-256")
model = AutoModelForImageClassification.from_pretrained("Kushagra07/autotrain-swinv2-tiny-patch4-window8-256", device_map="auto")Quick Links
Model Trained Using AutoTrain
- Problem type: Image Classification
Validation Metrics
loss: 0.2802155911922455
f1_macro: 0.7552413664079601
f1_micro: 0.9061113007852509
f1_weighted: 0.9035670983782715
precision_macro: 0.8498221458985794
precision_micro: 0.9061113007852509
precision_weighted: 0.9095288940815534
recall_macro: 0.7266443770545475
recall_micro: 0.9061113007852509
recall_weighted: 0.9061113007852509
accuracy: 0.9061113007852509
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Kushagra07/autotrain-swinv2-tiny-patch4-window8-256") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")