# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("hamdan07/UltraSound-Lung")
model = AutoModelForImageClassification.from_pretrained("hamdan07/UltraSound-Lung")Quick Links
Model Trained Using AutoTrain
- Problem type: Multi-class Classification
- Model ID: 3310291874
- CO2 Emissions (in grams): 1.3971
Validation Metrics
- Loss: 0.001
- Accuracy: 1.000
- Macro F1: 1.000
- Micro F1: 1.000
- Weighted F1: 1.000
- Macro Precision: 1.000
- Micro Precision: 1.000
- Weighted Precision: 1.000
- Macro Recall: 1.000
- Micro Recall: 1.000
- Weighted Recall: 1.000
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hamdan07/UltraSound-Lung") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")