Text Classification
Transformers
Safetensors
Portuguese
bert
toxicity-detection
NLP
classification
fine-tuning
Instructions to use CASLL/ToxiGuard with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CASLL/ToxiGuard with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CASLL/ToxiGuard")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CASLL/ToxiGuard") model = AutoModelForSequenceClassification.from_pretrained("CASLL/ToxiGuard") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9108444623cb8bfc7d8d4a8d29bfd819e6596b7c3642278687156d7c8a81b55e
- Size of remote file:
- 438 MB
- SHA256:
- fd709c01e17a52c47fa84c451f011625d0464a2ac7b80d26ba0f3953f1aea822
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.