Instructions to use OttoYu/Tree-ConditionHK with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OttoYu/Tree-ConditionHK with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="OttoYu/Tree-ConditionHK")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("OttoYu/Tree-ConditionHK") model = AutoModelForImageClassification.from_pretrained("OttoYu/Tree-ConditionHK") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c0c67e260e2b5c1f3aa93b38d99c7486d2c666c695ae90246fa89bbd2669bcab
- Size of remote file:
- 348 MB
- SHA256:
- 0d32dcdd8c9b6972053b8fb9afa1ec418a8089caffba8522d842b33ddfcaede8
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