Instructions to use angelala3252/decision-tree with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use angelala3252/decision-tree with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="angelala3252/decision-tree") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("angelala3252/decision-tree", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Upload config.json
Verified signaturee0a40e8 -
Upload config.json
Verified signature5965d2b -
Upload config.json
Verified signature74f9d95 -
Update README.md
Verified signaturec0ce0ac -
Create README.md
Verified signaturea181c7f -
Upload model.pkl with huggingface_hub
Verified signature8c30f33 -
Upload config.json with huggingface_hub
Verified signaturea526c46 -
Upload config.json with huggingface_hub
Verified signature0fae5c6 -
Upload config.json with huggingface_hub
Verified signatureec0bd14 -
Upload confusion_matrix.png with huggingface_hub
Verified signature5b1f4dc -
initial commit
Verified signatured81ef56