Instructions to use OttoYu/TreeClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OttoYu/TreeClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="OttoYu/TreeClassification") 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/TreeClassification") model = AutoModelForImageClassification.from_pretrained("OttoYu/TreeClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e81cd61e7677fc2005a4d9a1b333ac0825db63fec6eb17b239007dc1eeed9333
- Size of remote file:
- 348 MB
- SHA256:
- eb07799de70a84f150815872999c856b64e55fb4d0c99851029966529157a50f
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