Instructions to use ThermalVariations/tv-pv-module-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ThermalVariations/tv-pv-module-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ThermalVariations/tv-pv-module-classifier") 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("ThermalVariations/tv-pv-module-classifier") model = AutoModelForImageClassification.from_pretrained("ThermalVariations/tv-pv-module-classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d79398fe6be3d94aefce24a1fb48248db90234c0a45d8ef2c18e7279c14fca79
- Size of remote file:
- 343 MB
- SHA256:
- a3b3d44f661346f0e51df2fa13953f22c7beecf0a54824bca7f708e1436f7f8c
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