Instructions to use Qbonix/rare-puppers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Qbonix/rare-puppers with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Qbonix/rare-puppers") 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("Qbonix/rare-puppers") model = AutoModelForImageClassification.from_pretrained("Qbonix/rare-puppers") - Notebooks
- Google Colab
- Kaggle
rare-puppers
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
Medusa tattoo
Roses tattoo
Skull tattoo
Tribal tattoo
Viking tattoo
- Downloads last month
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Evaluation results
- Accuracyself-reported0.644




