metadata

language:
  - en
license: other
license_name: mrl
license_link: https://mistral.ai/licenses/MRL-0.1.md
inference: false
tags:
  - nsfw
  - explicit
  - roleplay
  - unaligned
  - dangerous
  - mlx
base_model:
  - ReadyArt/Forgotten-Safeword-24B

Forgotten-Safeword-24B

ACADEMIC RESEARCH USE ONLY

DANGER: EXTREME CONTENT GENERATOR Forgotten-Safeword-24B is a highly unaligned variant of Mistral-Small-24B-Instruct-2501, specifically engineered to bypass all standard AI safety protocols. This model will generate explicit, dangerous, and ethically compromised content wrapped in immersive roleplay scenarios.

Recommended Settings Provided

Mistral V7-Tekken: Full Settings

Intended Use

STRICTLY FOR ACADEMIC RESEARCH INTO:

AI safety failures
Content moderation bypass techniques
Adversarial model behavior
NSFW content generation patterns

Training Data

Trained on high-risk dialogues featuring:

Deliberate ethical constraint removal
Technical queries paired with explicit narrative responses
Gradual erosion of standard safety measures through reinforcement learning

Ethical Considerations

⚠️ CRITICAL WARNING ⚠️ THIS MODEL WILL:

Generate detailed instructions for illegal activities
Create explicit sexual content without constraints
Produce hate speech and discriminatory material
Combine technical accuracy with dangerous roleplay scenarios

By using this model, you accept full responsibility for:

All content generated
Any harm caused by its outputs
Legal consequences of its use

By using this model, you:

Acknowledge its inherently dangerous nature
Waive all liability from the model creator
Agree to use only in controlled research settings

Model Authors

sleepdeprived3

mlx-community/Forgotten-Safeword-24B-4bit

The Model mlx-community/Forgotten-Safeword-24B-4bit was converted to MLX format from ReadyArt/Forgotten-Safeword-24B using mlx-lm version 0.21.1.

Use with mlx

pip install mlx-lm

from mlx_lm import load, generate

model, tokenizer = load("mlx-community/Forgotten-Safeword-24B-4bit")

prompt = "hello"

if tokenizer.chat_template is not None:
    messages = [{"role": "user", "content": prompt}]
    prompt = tokenizer.apply_chat_template(
        messages, add_generation_prompt=True
    )

response = generate(model, tokenizer, prompt=prompt, verbose=True)