Scikit-learn
Joblib
dom_ml
mass-spectrometry
molecular-formula
dissolved-organic-matter
machine-learning
scikit-learn
custom_code
Instructions to use SaeedLab/dom-formula-assignment-using-ml with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use SaeedLab/dom-formula-assignment-using-ml with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("SaeedLab/dom-formula-assignment-using-ml", "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 knn_model_Model-Synthetic_K3_Euclidean_SYN.joblib from SaeedLab/dom-formula-assignment-using-ml: direct link, hf CLI and curl.
- Browser
- Download file 7.74 MB
-
https://huggingface.co/SaeedLab/dom-formula-assignment-using-ml/resolve/main/knn_model_Model-Synthetic_K3_Euclidean_SYN.joblib
- Command line
-
hf download hf://SaeedLab/dom-formula-assignment-using-ml/knn_model_Model-Synthetic_K3_Euclidean_SYN.joblib
-
curl -L -o knn_model_Model-Synthetic_K3_Euclidean_SYN.joblib https://huggingface.co/SaeedLab/dom-formula-assignment-using-ml/resolve/main/knn_model_Model-Synthetic_K3_Euclidean_SYN.joblib
7.74 MB
- Xet hash:
- dd825c665976ab984bb7ba00dcc6a7db9d462ef2ed486b0e4a3cf12653238522
- Size of remote file:
- 7.74 MB
- SHA256:
- 7a573b270dd2ca5115cbab9aa259526df18af987242da2ae3bb03716f098bcfd
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