Text Classification
Transformers
Safetensors
Portuguese
bert
Eval Results (legacy)
text-embeddings-inference
Instructions to use Silly-Machine/TuPy-Bert-Large-Binary-Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Silly-Machine/TuPy-Bert-Large-Binary-Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Silly-Machine/TuPy-Bert-Large-Binary-Classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Silly-Machine/TuPy-Bert-Large-Binary-Classifier") model = AutoModelForSequenceClassification.from_pretrained("Silly-Machine/TuPy-Bert-Large-Binary-Classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7b75c44abe44be8de0a0e857244c4a7efc91c14a3746ad82d6cee98593de76c2
- Size of remote file:
- 1.34 GB
- SHA256:
- 8bc5c017ce5cc0c3d0e6b0eac271a0a73c45322ef0a5a547ee9f3cb247cfe5c5
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