Text Classification
Transformers
Safetensors
Portuguese
bert
Eval Results (legacy)
text-embeddings-inference
Instructions to use Silly-Machine/TuPy-Bert-Base-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-Base-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-Base-Binary-Classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Silly-Machine/TuPy-Bert-Base-Binary-Classifier") model = AutoModelForSequenceClassification.from_pretrained("Silly-Machine/TuPy-Bert-Base-Binary-Classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 95b04058c58c9be8c647eb92e7b63f9cb367fd6fa4e927bf5c9408f8a8fad7da
- Size of remote file:
- 436 MB
- SHA256:
- 1b46b0263bf1721297a888405cf738a6017523240fcedbd4d72002fc510782de
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