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:
- a5e1a567147852c137a4d4d3dc5e96882b60a2ce20540fb94ba04eb7abe61feb
- Size of remote file:
- 832 Bytes
- SHA256:
- c1bd26704959b0fba1ac2dfd49be4a9b5cb81474204b90da2749c489c7a42d33
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