# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("defefekt/PDLO_Classifier")
model = AutoModelForImageClassification.from_pretrained("defefekt/PDLO_Classifier")Quick Links
ViTAMIn-O Custom Organoid Model
This model was trained using the ColabViTAMIn-O code-free infrastructure.
Model Details
- Base Architecture:
defefekt/ViTAMIn-O - Task Type:
Classification - Repository:
defefekt/PDLO_Classifier
Training Hyperparameters
- Seed:
42 - Epochs:
20 - Batch Size:
32
Evaluation Metrics (Test Set)
- Accuracy:
0.9250 - Global AUROC:
0.9881
This model card was auto-generated by the ViTAMIn-O pipeline to ensure reproducibility and open-science transparency.
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="defefekt/PDLO_Classifier") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")