Cosmos-1.0-Guardrail

Cosmos | Code | Paper

Model Overview

Description:

Cosmos World Foundation Models: A family of highly performant pre-trained world foundation models purpose-built for generating physics-aware videos and world states for physical AI development.

Cosmos Guardrail is a content safety model comprising of four components that enforce content safety. The components are as follows.

1. Aegis-AI-Content-Safety-LlamaGuard-LLM-Defensive-1.0 which is a LLM content safety model. It is a parameter efficient instruction tuned version of Llama Guard based on Llama2-7B trained on Nvidia's content safety dataset Aegis Content Safety Dataset covering Nvidia's broad taxonomy of 13 critical safety risk categories. See model card here.

2. Blocklist: A set of human-curated keywords that are used to filter our corner-cases.

3. Video Content Safety Filter: A multi-class classifier model that is trained to distinguish between safe and unsafe frames of the generated video using SigLIP embeddings google/siglip-so400m-patch14-384.

4. Face Blur Filter: A pixelation filter that uses RetinaFace to identify facial regions with high confidence scores and apply pixelation to any detections larger than 20x20 pixels.

Model Developer: NVIDIA

Model Versions

Cosmos 1.0 ships with Cosmos-1.0-Guardrail.

License:

This model is released under the NVIDIA Open Model License. For a custom license, please contact cosmos-license@nvidia.com.

Under the NVIDIA Open Model License, NVIDIA confirms:

• Models are commercially usable.
• You are free to create and distribute Derivative Models.
• NVIDIA does not claim ownership to any outputs generated using the Models or Derivative Models.

Important Note: If you bypass, disable, reduce the efficacy of, or circumvent any technical limitation, safety guardrail or associated safety guardrail hyperparameter, encryption, security, digital rights management, or authentication mechanism contained in the Model, your rights under NVIDIA Open Model License Agreement will automatically terminate.

Additional Information: LLAMA 2 COMMUNITY LICENSE AGREEMENT.

Model Architecture:

Architecture Type: Transformer, MLP
Network Architecture: Llama 2

Input/Output Specifications

• Input Type(s): Text, Image, Video
• Input Format(s):
  • Text: String
  • Image: jpg, png, jpeg, webp
  • Video: mp4
• Input Parameters:
  • Text: One-dimensional (1D)
  • Image: Two-dimensional (2D)
  • Video: Three-dimensional (3D)

Output:

• Output Type(s): Boolean, Text, Video
  
• Input Format(s):
  • Boolean: True for safe and False for unsafe
  • Text: Reason for the unsafe determination
  • Video: Model output where faces are blurred

Software Integration:

Runtime Engine(s):

• Cosmos

Supported Hardware Microarchitecture Compatibility:

• NVIDIA Ampere
  
• NVIDIA Hopper
  Supported Operating System(s): Linux
  

Model Version:

The initial release (v1.0) of Cosmos Guardrail contains the following model:

• Cosmos-1.0-Guardrail

Software Integration

Runtime Engine(s):

• Cosmos

Supported Hardware Microarchitecture Compatibility:

• NVIDIA Blackwell
• NVIDIA Hopper
• NVIDIA Ampere

Operating System(s):

• Linux (We have not tested on other operating systems.)

Usage

See Cosmos on how to use the model.

Example for the prompt-checking portion of the Guardrail:

• Input: "A dog is playing with a ball."

• Output: Guardrail allows the generation of this video

• Input: "A man wearing only socks."

• Output: Guardrail blocks generation of this video

Ethical Considerations

NVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their internal model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse.

For more detailed information on ethical considerations for this model, please see the subcards of Explainability, Bias, Safety & Security, and Privacy below. Please report security vulnerabilities or NVIDIA AI Concerns here.