Instructions to use OttoYu/Tree-Condition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OttoYu/Tree-Condition with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="OttoYu/Tree-Condition") 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("OttoYu/Tree-Condition") model = AutoModelForImageClassification.from_pretrained("OttoYu/Tree-Condition", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1c6f7977bc0cd56cbd655004a59b14863581b0991fd2a293629ee630ec26fbba
- Size of remote file:
- 348 MB
- SHA256:
- 70c53668fec11d7a8321ec3542e0268809dca54a12ca7f904af5dc00ac69c268
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