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")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("OttoYu/TreeClassification") model = AutoModelForImageClassification.from_pretrained("OttoYu/TreeClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from OttoYu/TreeClassification: direct link, hf CLI and curl.
- Browser
- Download file 348 MB
-
https://huggingface.co/OttoYu/TreeClassification/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://OttoYu/TreeClassification@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/OttoYu/TreeClassification/resolve/refs%2Fpr%2F1/model.safetensors
348 MB
- Xet hash:
- b3c4d76f710bc9d16a4b9840d0498534e35563a800cfdcb01bfa35fdfcc906ea
- Size of remote file:
- 348 MB
- SHA256:
- 38d1a4dbc740fdf3055cd86fd783c9be0e822b88a75aee5aa515f3758fd5783f
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