Text Classification
Transformers
PyTorch
Safetensors
Portuguese
bert
toxicity
alignment
text-embeddings-inference
Instructions to use nicholasKluge/ToxiGuardrailPT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nicholasKluge/ToxiGuardrailPT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nicholasKluge/ToxiGuardrailPT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nicholasKluge/ToxiGuardrailPT") model = AutoModelForSequenceClassification.from_pretrained("nicholasKluge/ToxiGuardrailPT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 438722c555f5d5f1d858cd76a11284f13abc88ed00984bd86eb01eaf2ebddb61
- Size of remote file:
- 436 MB
- SHA256:
- 44e627928229a78836fcff7135d16e8ff4e63fe2309df934e31bfa508178d276
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