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:
- 4f5468f88e920791eda4d8378572da7ce6bb09e316c3aee2ed36eeb6c2819f6a
- Size of remote file:
- 1.6 kB
- SHA256:
- c7d0d548c66a4c312236484d1ac972be8b5617b4d7f6bd0e6c48484e20a7732c
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