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
File size: 498 Bytes
211dde8 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | from transformers import PretrainedConfig
class DomMLConfig(PretrainedConfig):
model_type = "dom_ml"
def __init__(
self,
model_name="Synthetic_K3_Euclidean_Ensemble",
model_file=None,
feature_names=None,
model_kind=None,
**kwargs,
):
super().__init__(**kwargs)
self.model_name = model_name
self.model_file = model_file
self.model_kind = model_kind
self.feature_names = feature_names or ["mass"]
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