Instructions to use undertheseanlp/sen-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use undertheseanlp/sen-1 with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("undertheseanlp/sen-1", "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
Commit History
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Add sentiment models v1.2.0 with Vietnamese preprocessing
- Train sentiment-general (VLSP2016+UTS2017): 92.11% UTS2017, 70.86% VLSP2016 - Train sentiment-bank (UTS2017): 70.65% accuracy - Add preprocessing: lowercase, teencode expansion, negation marking, repeated char normalization - Update TECHNICAL_REPORT.md to v1.2.0 with full experiment results - Track .bin files with LFS/Xet storage Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>b5fd35d