# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("howdyaendra/xblock-large-patch3-224")
model = AutoModelForImageClassification.from_pretrained("howdyaendra/xblock-large-patch3-224")Quick Links
Model Trained Using AutoTrain
- Problem type: Image Classification
Validation Metrics
loss: 0.37855324149131775
f1_macro: 0.86094260720702
f1_micro: 0.8886217948717948
f1_weighted: 0.883196165156119
precision_macro: 0.8961444617693151
precision_micro: 0.8886217948717948
precision_weighted: 0.8922651559280282
recall_macro: 0.8524486181675118
recall_micro: 0.8886217948717948
recall_weighted: 0.8886217948717948
accuracy: 0.8886217948717948
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="howdyaendra/xblock-large-patch3-224") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")