Text Classification
Transformers
Joblib
Portuguese
streamlit
multi-label-classification
gradient-boosting
active-learning
bertimbau
municipal-documents
meeting-minutes
Instructions to use anonymous12321/Council_Topics_Classifier_PT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anonymous12321/Council_Topics_Classifier_PT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="anonymous12321/Council_Topics_Classifier_PT")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("anonymous12321/Council_Topics_Classifier_PT", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 892b98027ca81cb2dbe42374f9c3a54280e47283c32b9dda928818ffe8b51498
- Size of remote file:
- 1.91 MB
- SHA256:
- d8ca35ecf58dbf92d27ae4f23ae42dedcf468299eb4f7e012e89b73b9c3c4660
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