Instructions to use yzhuang/MetaTree with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yzhuang/MetaTree with Transformers:
# Load model directly from transformers import AutoTokenizer, LlamaForMetaTree tokenizer = AutoTokenizer.from_pretrained("yzhuang/MetaTree") model = LlamaForMetaTree.from_pretrained("yzhuang/MetaTree") - Notebooks
- Google Colab
- Kaggle
Added missing declaration for decision_tree_forest (#1)
Browse files- Added missing declaration for decision_tree_forest (d8e632ef6dfc0d0fd285f7434021b34c45489eda)
Co-authored-by: Akshat Gupta <something456@users.noreply.huggingface.co>
README.md
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@@ -39,7 +39,8 @@ config = AutoConfig.from_pretrained(model_name_or_path)
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model = MetaTree.from_pretrained(
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model_name_or_path,
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config=config,
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)
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# Load Datasets
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X, y, feature_names = imodels.get_clean_dataset('fico', data_source='imodels')
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model = MetaTree.from_pretrained(
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model_name_or_path,
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config=config,
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)
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decision_tree_forest = DecisionTreeForest()
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# Load Datasets
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X, y, feature_names = imodels.get_clean_dataset('fico', data_source='imodels')
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