# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("defefekt/ViTAMIn-O")
model = AutoModelForImageClassification.from_pretrained("defefekt/ViTAMIn-O")Quick Links
ViTAMIn-O Generalist Model
This is the official baseline model, trained and used for inference in the corresponding paper:
ViTAMIn-O: Democratizing computer vision-based machine learning for stem cell research
Model Details
- Base Architecture:
microsoft/swin-large-patch4-window7-224 - Task Type:
Classification - Repository:
defefekt/ViTAMIn-O
Training Hyperparameters
- Seed:
42 - Epochs:
50 - Batch Size:
64
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="defefekt/ViTAMIn-O") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")