Instructions to use Professor/Plant_Classification_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Professor/Plant_Classification_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Professor/Plant_Classification_model") 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("Professor/Plant_Classification_model") model = AutoModelForImageClassification.from_pretrained("Professor/Plant_Classification_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a1124ebf03edcca9e1cb6c70b229ded371741acea4a2cfad4dea94e48bfafce5
- Size of remote file:
- 343 MB
- SHA256:
- cb95b3729080fc00b385aebb8e957a9194b46a252d1d3e672c3bb930d555963b
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