Instructions to use steven123/Check_Gum_Teeth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use steven123/Check_Gum_Teeth with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="steven123/Check_Gum_Teeth") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("steven123/Check_Gum_Teeth") model = AutoModelForImageClassification.from_pretrained("steven123/Check_Gum_Teeth") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification
processor = AutoImageProcessor.from_pretrained("steven123/Check_Gum_Teeth")
model = AutoModelForImageClassification.from_pretrained("steven123/Check_Gum_Teeth")Quick Links
Check_Gum_Teeth
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_Gum
Good_Gum
- Downloads last month
- 10
Evaluation results
- Accuracyself-reported1.000


# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="steven123/Check_Gum_Teeth") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")