# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("howdyaendra/xblock-base-patch1-224")
model = AutoModelForImageClassification.from_pretrained("howdyaendra/xblock-base-patch1-224")Quick Links
Model Trained Using AutoTrain
- Problem type: Image Classification
Validation Metrics
loss: 0.4469132423400879
f1_macro: 0.8236777117298302
f1_micro: 0.829560585885486
f1_weighted: 0.8289271724966029
precision_macro: 0.8243514221166717
precision_micro: 0.829560585885486
precision_weighted: 0.8313607282611274
recall_macro: 0.8260057947019868
recall_micro: 0.829560585885486
recall_weighted: 0.829560585885486
accuracy: 0.829560585885486
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="howdyaendra/xblock-base-patch1-224") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")