Instructions to use yanlanh/subject-clf-tfidf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use yanlanh/subject-clf-tfidf with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("yanlanh/subject-clf-tfidf", "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
subject-clf-tfidf
Multi-label subject classifier -- labels: English, Maths, Science, Civics, Geology.
- base:
TF-IDF (word+char n-grams) -> one-vs-rest LogisticRegression - trained on
yanlanh/multilabel-subject-dataset@5d8dc42
import joblib
from huggingface_hub import hf_hub_download
pipe = joblib.load(hf_hub_download("yanlanh/subject-clf-tfidf", "pipe.joblib"))
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