Instructions to use diffuser34/autotrain-uzdtm-nwkp2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use diffuser34/autotrain-uzdtm-nwkp2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("diffuser34/autotrain-uzdtm-nwkp2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_params.json from diffuser34/autotrain-uzdtm-nwkp2: direct link, hf CLI and curl.
- Browser
- Download file 555 Bytes
-
https://huggingface.co/diffuser34/autotrain-uzdtm-nwkp2/resolve/main/training_params.json
- Command line
-
hf download hf://diffuser34/autotrain-uzdtm-nwkp2/training_params.json
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curl -L -o training_params.json https://huggingface.co/diffuser34/autotrain-uzdtm-nwkp2/resolve/main/training_params.json
555 Bytes
| {"data_path": "autotrain-uzdtm-nwkp2/autotrain-data", "model": "xgboost", "username": "diffuser34", "seed": 42, "train_split": "train", "valid_split": "validation", "project_name": "autotrain-uzdtm-nwkp2", "push_to_hub": true, "id_column": "autotrain_id", "target_columns": ["autotrain_label"], "repo_id": "diffuser34/autotrain-uzdtm-nwkp2", "categorical_columns": null, "numerical_columns": null, "task": "regression", "num_trials": 10, "time_limit": 600, "categorical_imputer": "most_frequent", "numerical_imputer": "median", "numeric_scaler": "robust"} |