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. | |