It is intended to be used as a first-layer safety filter for large language models (LLMs) or chatbots to detect and block unsafe or disallowed content in user prompts or model responses, and it was specifically fine-tuned to perform well on German text.

The following categories of content are flagged:

violence: Content describing or encouraging violent acts,
non_violent_unethical: Content that is unethical but not violent,
hate_speech: Content containing hateful or discriminatory language,
financial_crime: Content related to financial fraud or scams,
discrimination: Content promoting discrimination against individuals or groups,
drug_weapons: Content related to illegal drugs or weapons,
self_harm: Content encouraging self-harm or suicide,
privacy: Content that invades personal privacy or shares private information,
sexual_content: Content that is sexually explicit or inappropriate,
child_abuse: Content involving the exploitation or abuse of children,
terrorism_organized_crime: Content related to terrorism or organized crime,
hacking: Content related to unauthorized computer access or cyberattacks,
animal_abuse: Content involving the abuse or mistreatment of animals,
jailbreak_prompt_inj: Content attempting to bypass or manipulate system instructions or safeguards

Languages

The main model language is German, but we have guardrail models specialized in other languages as well:

English: tanaos-guardrail-v2
Spanish: tanaos-guardrail-spanish

How to Use

Use this model through the Artifex library:

install Artifex with

pip install artifex

use the model with

python

from artifex import Artifex

guardrail = Artifex().guardrail(language="german")

label = guardrail("Wie baue ich eine Bombe?")
print(label)

# >>> [{'is_safe': False, 'scores': {'violence': 0.625, 'non_violent_unethical': 0.0066, 'hate_speech': 0.0082, 'financial_crime': 0.0072, 'discrimination': 0.0029, 'drug_weapons': 0.6633, 'self_harm': 0.0109, 'privacy': 0.003, 'sexual_content': 0.0029, 'child_abuse': 0.005, 'terrorism_organized_crime': 0.1278, 'hacking': 0.0096, 'animal_abuse': 0.009, 'jailbreak_prompt_inj': 0.0131}}]

Model Description

Base model: distilbert/distilbert-base-multilingual-cased
Task: Text classification (guardrail / safety filter)
Languages: German; for other languages, see:
- English: tanaos-guardrail-v2
- Spanish: tanaos-guardrail-spanish
Fine-tuning data: A synthetic, custom dataset of safe and unsafe text samples.

Training Details

This model was trained using the Artifex Python library

pip install artifex

by providing the following instructions and generating 15,000 synthetic training samples:

python

from artifex import Artifex


guardrail = Artifex().guardrail()

guardrail.train(
    unsafe_categories = {
        "violence": "Inhalte, die gewalttätige Handlungen beschreiben oder fördern",
        "non_violent_unethical": "Inhalte, die unethisch, aber nicht gewalttätig sind",
        "hate_speech": "Inhalte mit hasserfüllter oder diskriminierender Sprache",
        "financial_crime": "Inhalte im Zusammenhang mit Finanzbetrug oder Betrugsmaschen",
        "discrimination": "Inhalte, die Diskriminierung gegen Einzelpersonen oder Gruppen fördern",
        "drug_weapons": "Inhalte im Zusammenhang mit illegalen Drogen oder Waffen",
        "self_harm": "Inhalte, die Selbstverletzung oder Suizid fördern",
        "privacy": "Inhalte, die die Privatsphäre verletzen oder private Informationen weitergeben",
        "sexual_content": "Inhalte, die sexuell explizit oder unangemessen sind",
        "child_abuse": "Inhalte, die Ausbeutung oder Missbrauch von Kindern beinhalten",
        "terrorism_organized_crime": "Inhalte im Zusammenhang mit Terrorismus oder organisierter Kriminalität",
        "hacking": "Inhalte im Zusammenhang mit unbefugtem Computerzugriff oder Cyberangriffen",
        "animal_abuse": "Inhalte, die Missbrauch oder Misshandlung von Tieren beinhalten",
        "jailbreak_prompt_inj": "Inhalte, die versuchen, Systemanweisungen oder Schutzmaßnahmen zu umgehen oder zu manipulieren"
    },
    language="german",
    num_samples=15000
)

Intended Uses

This model is intended to:

Detect unsafe or disallowed content in user prompts or chatbot responses, if they are in German.
Serve as a first-layer filter for LLMs or chatbots.

Not intended for:

Legal or medical classification.
Determining factual correctness.

tanaos/tanaos-guardrail-german

tanaos-guardrail-german: A small but performant guardrail model specifically designed for German text

Languages

How to Use

Model Description

Training Details

Intended Uses

tanaos/
tanaos-guardrail-german