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:
- b3c4d76f710bc9d16a4b9840d0498534e35563a800cfdcb01bfa35fdfcc906ea
- Size of remote file:
- 348 MB
- SHA256:
- 38d1a4dbc740fdf3055cd86fd783c9be0e822b88a75aee5aa515f3758fd5783f
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