Image Classification
Transformers
TensorBoard
Safetensors
PyTorch
vit
huggingpics
Eval Results (legacy)
# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("zabir735/seed-VIT-patch16")
model = AutoModelForImageClassification.from_pretrained("zabir735/seed-VIT-patch16")Quick Links
seed-VIT-patch16
Autogenerated by HuggingPics🤗🖼️
Create your own image classifier for anything by running the demo on Google Colab.
Report any issues with the demo at the github repo.
Example Images
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Evaluation results
- Accuracyself-reported0.973
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="zabir735/seed-VIT-patch16") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")