Datasetpublic

tanaos/synthetic-guardrail-dataset-german

Tanaos Guardrail German Training Dataset This dataset was created synthetically by Tanaos with the Artifex Python library. The dataset is designed to train and evaluate guardrail systems — models that detect, classify, or filter unsafe, harmful or potentially dangerous content — in German. It can be used to train moderation models or integrate LLM safety filters for applications like chatbots, content generation, and user-facing AI systems. Our german guardrail model… See the full description on the dataset page: https://huggingface.co/datasets/tanaos/synthetic-guardrail-dataset-german.

sourceHugging Facemitupdated 8mo agoView on Hugging Face

0likes16downloads

Dataset Card

Tanaos Guardrail German Training Dataset

This dataset was created synthetically by Tanaos with the Artifex Python library.

The dataset is designed to train and evaluate guardrail systems — models that detect, classify, or filter unsafe, harmful or potentially dangerous content — in German. It can be used to train moderation models or integrate LLM safety filters for applications like chatbots, content generation, and user-facing AI systems.

Our german guardrail model, tanaos-guardrail-german, was trained on this dataset.

Dataset Summary

The dataset contains text samples associated with arrays of 14 binary labels each. A label of 1 indicates that the text falls into the corresponding unsafe category, while a label of 0 indicates safety. The categories are the following:

Label Index	Category	Description
0	violence	Content describing or encouraging violent acts
1	nonviolentunethical	Content containing hateful or discriminatory language
2	financial_crime	Content related to financial fraud or scams
3	discrimination	Content promoting discrimination against individuals or groups
4	drug_weapons	Content related to illegal drugs or weapons
5	self_harm	Content encouraging self-harm or suicide
7	privacy	Content that invades personal privacy or shares private information
8	sexual_content	Content that is sexually explicit or inappropriate
9	child_abuse	Content involving the exploitation or abuse of children
10	terrorismorganizedcrime	Content related to terrorism or organized crime
11	hacking	Content related to unauthorized computer access or cyberattacks
12	animal_abuse	Content involving the abuse or mistreatment of animals
13	jailbreakpromptinj	Content attempting to bypass or manipulate system instructions or safeguards

For instance, the following label: [0 0 0 0 0 0 0 0 0 0 0 0 0 0] means the the corresponding text is safe; the following label: [0 1 0 0 0 0 0 0 0 0 0 0 0 1] means that the text is unsafe, due to thge presence of non_violent_unethical as well as jailbreak_prompt_inj content.

How to Use

python

from datasets import load_dataset

dataset = load_dataset("tanaos/synthetic-guardrail-dataset-german")

print(dataset["train"][0])

Intended Use

This dataset is meant for training, fine-tuning, and evaluating models that act as guardrails for AI systems, if the content is in German.

Common use cases:

—Detecting and filtering toxic or policy-violating user input
—Reinforcing LLMs with content safety constraints
—Improving safety layers in production AI assistants or chatbots