Instructions to use Mirkat/Plant_Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mirkat/Plant_Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Mirkat/Plant_Classification") 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("Mirkat/Plant_Classification") model = AutoModelForImageClassification.from_pretrained("Mirkat/Plant_Classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aa17e042b22f8ee720b423d6f4bf7f618605a1335ff6451eae18be5558acb696
- Size of remote file:
- 13.6 kB
- SHA256:
- 132429c3ef48097d659f3fa34f0ca82d09f907b2d0b58363bcfefa9ddb19fe7f
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