Instructions to use roksechs/sheet-cell-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use roksechs/sheet-cell-classifier with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("roksechs/sheet-cell-classifier", "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
sheet-cell-classifier
RandomForest cell role classifier for Excel spreadsheets, used by sheet-call-tree.
Model
Predicts whether a spreadsheet cell is a header (0) or data (1). Trained on CTC (CIUS + SAUS) and ENTRANT datasets.
Features (23): gap-proximity (dist_above, dist_left), row/col numeric fractions, format fields (bold, italic, colors, borders, alignment, data type), value type flags.
Usage
from huggingface_hub import hf_hub_download
import joblib
model_path = hf_hub_download(repo_id="roksechs/sheet-cell-classifier", filename="cell_classifier.joblib")
clf = joblib.load(model_path)
sheet-call-tree >= 0.1.2 downloads and uses this model automatically.
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