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-patch32")
model = AutoModelForImageClassification.from_pretrained("zabir735/seed-VIT-patch32")Quick Links
seed-VIT-patch32
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
Bad oil palm seed
Good oil palm seed
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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-patch32") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")