# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("MichalGas/instrument-0")
model = AutoModelForImageClassification.from_pretrained("MichalGas/instrument-0", device_map="auto")Quick Links
Model Trained Using AutoTrain
- Problem type: Image Classification
Validation Metricsg
loss: nan
f1_macro: 0.05573770491803279
f1_micro: 0.20078740157480315
f1_weighted: 0.06714857364140958
precision_macro: 0.03346456692913386
precision_micro: 0.20078740157480315
precision_weighted: 0.040315580631161266
recall_macro: 0.16666666666666666
recall_micro: 0.20078740157480315
recall_weighted: 0.20078740157480315
accuracy: 0.20078740157480315
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="MichalGas/instrument-0") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")