# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("howdyaendra/xblock-large-patch2-224")
model = AutoModelForImageClassification.from_pretrained("howdyaendra/xblock-large-patch2-224")Quick Links
Model Trained Using AutoTrain
- Problem type: Image Classification
Validation Metrics
loss: 0.4315283000469208
f1_macro: 0.6149830093941424
f1_micro: 0.8602430555555556
f1_weighted: 0.8515059109185544
precision_macro: 0.7610988679415244
precision_micro: 0.8602430555555556
precision_weighted: 0.8532444856848228
recall_macro: 0.5527145295483504
recall_micro: 0.8602430555555556
recall_weighted: 0.8602430555555556
accuracy: 0.8602430555555556
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="howdyaendra/xblock-large-patch2-224") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")