Text Classification
Transformers
PyTorch
Safetensors
Portuguese
Trained with AutoTrain
Eval Results (legacy)
Instructions to use inctdd/told_br_binary_sm_bertimbau with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use inctdd/told_br_binary_sm_bertimbau with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="inctdd/told_br_binary_sm_bertimbau")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("inctdd/told_br_binary_sm_bertimbau", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4276ee27815c211ad7bb0624f36871ef44bdd513dd6405223a2442bab7e6069d
- Size of remote file:
- 436 MB
- SHA256:
- 751713e64da642b2987565235c2365ad187ffe73464be5610397be9b16bc4652
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