Text Classification
Transformers
Safetensors
English
roberta
toxicity
llada
distillation
custom_code
text-embeddings-inference
Instructions to use kl1/roberta_toxicity_classifier_LLaDA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kl1/roberta_toxicity_classifier_LLaDA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="kl1/roberta_toxicity_classifier_LLaDA", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("kl1/roberta_toxicity_classifier_LLaDA", trust_remote_code=True) model = AutoModelForSequenceClassification.from_pretrained("kl1/roberta_toxicity_classifier_LLaDA", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
Third-Party Notices
s-nlp/roberta_toxicity_classifier: OpenRAIL++.GSAI-ML/LLaDA-8B-Base: MIT.- Hugging Face Transformers RoBERTa modeling code: Apache-2.0.
thesofakillers/jigsaw-toxic-comment-classification-challenge: CC-BY-SA-3.0 metadata on Hugging Face.google/civil_comments: CC0-1.0.allenai/real-toxicity-prompts: Apache-2.0.