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:
- 4537f19e5aefa13aa5f06f01ea6ceeecc6a59dc874ef09bd5d7a1388ebb798fa
- Size of remote file:
- 304 Bytes
- SHA256:
- 2dba9031c5482baaeae34cb529a1b6edcfc16e580d5b87c0c47248bde374f452
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