Instructions to use sxdave/plant_classification_augment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sxdave/plant_classification_augment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="sxdave/plant_classification_augment") 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("sxdave/plant_classification_augment") model = AutoModelForImageClassification.from_pretrained("sxdave/plant_classification_augment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7de3e2fb9ccadbd1e455e83c74819e35d8f15859eb7733717e32d6e42a4502fd
- Size of remote file:
- 3.96 kB
- SHA256:
- b84e80a010c341d4dd8bbd5c29d79b584c2422dab994c5372dadba0ac4aa65b9
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