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:
- ad9cc26aa61f89c003659898c7f93d7aca3b175da627a38cdaff77b1fd80f7fa
- Size of remote file:
- 1.06 kB
- SHA256:
- f627496766215c292bc1d6ceecb7b0e07bcc89f3a3d097e9d4c5b8a4241c674f
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