Image Classification
Transformers
TensorBoard
Safetensors
PyTorch
vit
huggingpics
Eval Results (legacy)
# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("miittnnss/sweets")
model = AutoModelForImageClassification.from_pretrained("miittnnss/sweets")Quick Links
sweets
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
candy
chocolate
cotton candy
ice cream
lollipop
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Evaluation results
- Accuracyself-reported0.616
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="miittnnss/sweets") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")