Image Classification
Transformers
TensorBoard
Safetensors
PyTorch
vit
huggingpics
Eval Results (legacy)
# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("yeonghun2/clasfy_error")
model = AutoModelForImageClassification.from_pretrained("yeonghun2/clasfy_error")Quick Links
clasfy_error
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
error
normal
- Downloads last month
- 3
Evaluation results
- Accuracyself-reported1.000
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="yeonghun2/clasfy_error") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")