Instructions to use SummerChiam/pond_image_classification_11 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SummerChiam/pond_image_classification_11 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="SummerChiam/pond_image_classification_11") 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("SummerChiam/pond_image_classification_11") model = AutoModelForImageClassification.from_pretrained("SummerChiam/pond_image_classification_11") - Notebooks
- Google Colab
- Kaggle
pond_image_classification_11
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
Algae0
Boiling0
BoilingNight0
Normal0
NormalCement0
NormalNight0
NormalRain0
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Evaluation results
- Accuracyself-reported0.995






