Text Classification
Transformers
Safetensors
English
bert
safety
moderation
content-moderation
toxicity
guardrails
nvidia
nemotron
small-model
on-device
Eval Results (legacy)
text-embeddings-inference
Instructions to use SupraLabs/SupraSafety-18M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SupraLabs/SupraSafety-18M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SupraLabs/SupraSafety-18M")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SupraLabs/SupraSafety-18M") model = AutoModelForSequenceClassification.from_pretrained("SupraLabs/SupraSafety-18M") - Notebooks
- Google Colab
- Kaggle
Safe/unsafe categories
#4
by python-processing-unit - opened
What categories of prompts does it classify as unsafe?
Your examples included weapons manufacturing, hacking, and self-harm.
All of the prompts in the dataset.
LH-Tech-AI changed discussion status to closed