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:
- afe4fdd78ab7472347b3fdbe75bb8169b979b7ee6e1d85d4c1e5d683d9cb95a0
- Size of remote file:
- 678 kB
- SHA256:
- 112d88e0707640edfa50d95d8b2271da3f13f6c7e8a441018891aa52b36d67b4
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