Instructions to use lazyturtl/WEC-types with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lazyturtl/WEC-types with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="lazyturtl/WEC-types") 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("lazyturtl/WEC-types") model = AutoModelForImageClassification.from_pretrained("lazyturtl/WEC-types") - Notebooks
- Google Colab
- Kaggle
WEC-types
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
Attenuators
Oscillating water column
Overtopping Devices
Point Absorber
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Evaluation results
- Accuracyself-reported0.783



