Instructions to use Delower/dpp4-pic50-extra-trees with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use Delower/dpp4-pic50-extra-trees with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("Delower/dpp4-pic50-extra-trees", "sklearn_model.joblib") ) # only load pickle files from sources you trust # read more about it here https://skops.readthedocs.io/en/stable/persistence.html - Notebooks
- Google Colab
- Kaggle
Download config.json from Delower/dpp4-pic50-extra-trees: direct link, hf CLI and curl.
- Browser
- Download file 484 Bytes
-
https://huggingface.co/Delower/dpp4-pic50-extra-trees/resolve/main/config.json
- Command line
-
hf download hf://Delower/dpp4-pic50-extra-trees/config.json
-
curl -L -o config.json https://huggingface.co/Delower/dpp4-pic50-extra-trees/resolve/main/config.json
484 Bytes
| { | |
| "model_name": "extra-trees-morgan1024-physchem", | |
| "features": [ | |
| "morgan1024", | |
| "physchem" | |
| ], | |
| "framework": "scikit-learn", | |
| "model_file": "extra_trees_morgan1024_physchem.pkl", | |
| "model_type": "sklearn Pipeline (ColumnTransformer + ExtraTreesRegressor)", | |
| "physchem_order": [ | |
| "MolWt", | |
| "MolLogP", | |
| "TPSA", | |
| "NumHDonors", | |
| "NumHAcceptors", | |
| "NumRotatableBonds" | |
| ], | |
| "feature_columns": "feature_0..feature_1029 (Morgan 1024 first, physchem last)" | |
| } |