Sponsored by
Vmake Labs Video Enhancer
-Vmake Labs Video Enhancer uses AI to improve video quality, restore details, reduce blur, and upscale videos to 8K.
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 three components that enforce content safety. The components are as follows.
Blocklist: A set of human-curated keywords that are used to filter our corner-cases.
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
.
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.
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.
Model Architecture:
Video Content Safety Filter
: MLP backbone using SigLIP embeddings
Face Blur Filter
: ResNet-50 backbone
Input/Output Specifications
Input Type(s)
: Text, Video
Input Format(s)
:
Text (str): Input prompt
Video (np.ndarray): Video frames
Input Parameters
:
Text: One-dimensional (1D)
Video: Three-dimensional (3D)
Output:
Output Type(s):
Boolean, Text, Video
Output Format(s)
:
Boolean: True for safe and False for unsafe
Text (str): Reason for the unsafe determination
Video (np.ndarray): Processed video frames where faces are blurred
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
.
Plus Plus (++) Promise
We value you, the datasets, the diversity they represent, and what we have been entrusted with. This model and its associated data have been:
Verified to comply with current applicable disclosure laws, regulations, and industry standards.
Verified to comply with applicable privacy labeling requirements.
Annotated to describe the collector/source (NVIDIA or a third-party).
Characterized for technical limitations.
Reviewed to ensure proper disclosure is accessible to, maintained for, and in compliance with NVIDIA data subjects and their requests.
Reviewed before release.
Tagged for known restrictions and potential safety implications.
Bias
Field
Response
Participation considerations from adversely impacted groups
protected classes
in model design and testing:
None
Measures taken to mitigate against unwanted bias:
None
Explainability
Field
Response
Intended Application & Domain:
Content moderation for world generation
Model Type:
Ensemble
Intended Users:
Generative AI developers for world generation models
Output:
Boolean
Describe how the model works:
Check safety of input prompts or generated videos and output a safety classification
Technical Limitations:
The model may not moderate input prompt accurately and may have incorrect responses.
Verified to have met prescribed NVIDIA quality standards:
Yes
Performance Metrics:
Human Evaluation
Potential Known Risks:
The model's output can potentially classify content considered toxic, offensive, or indecent as safe.
The Principle of least privilege (PoLP) is applied limiting access for dataset generation and model development. Restrictions enforce dataset access during training, and dataset license constraints adhered to. Model checkpoints are made available on Hugging Face, and may become available on cloud providers' model catalog.
Runs of Arsh9210 Cosmos-1.0-Guardrail on huggingface.co
17
Total runs
-2
24-hour runs
-3
3-day runs
-8
7-day runs
3
30-day runs
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