Cosmos-Predict1-7B-Decoder-DV8x16x16ToCV8x8x8-720p

Cosmos | Code | Paper | Paper Website

Model Overview

Description:

Cosmos-Predict1-7B-Decoder-DV8x16x16ToCV8x8x8-720p is a diffusion decoder model that can improve outputs of Cosmos-Predict1 models with more fine-grained details. This model is ready for commercial use.

Model Developer: NVIDIA

Model Versions

In this release, the Cosmos Diffusion Decoder includes the following models:

Cosmos-Predict1-7B-Decoder-DV8x16x16ToCV8x8x8-720p

License:

This model is released under the NVIDIA Open Model License. For a custom license, please contact [email protected].

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:

Cosmos-Predict1-7B-Decoder-DV8x16x16ToCV8x8x8-720p is a diffusion transformer model designed for video denoising within the latent space. The network is composed of interleaved self-attention, cross-attention and feedforward layers as its building blocks. The cross-attention layers allow the model to condition on input text throughout the denoising process. Before each layers, adaptive layer normalization is applied to embed the time information for denoising.

Input/Output Specifications

Input
- Input Type(s): Tokens
- Input Format(s): Integer Tensor
- Input Parameters: Three-dimensional (3D)
- Other Properties Related to Input:
  - Integer indices ranging from 0 to 63,999
  - Should be the tokens generated by Cosmos-Tokenize1-DV8x16x16-720p
Output
- Output Type(s): Tokens
- Output Format(s): Float Tensor
- Output Parameters: Three-dimensional (3D)
- Other Properties Related to Output:
  - Continuous-valued feature vectors with a dimensionality of 16
  - The output tokens can be used as input for the decoder of Cosmos-Tokenize1-CV8x8x8-360p

Software Integration

Runtime Engine(s):

Cosmos-Predict1

Supported Hardware Microarchitecture Compatibility:

NVIDIA Blackwell
NVIDIA Hopper
NVIDIA Ampere

Note: We have only tested doing inference with BF16 precision.

Operating System(s):

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

Usage

See Cosmos-Predict1 for details.

Evaluation

Please see our technical paper for detailed evaluations.

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:	World Generation
Model Type:	Transformer
Intended Users:	Physical AI developers
Output:	Videos
Describe how the model works:	Generates videos based on video inputs
Technical Limitations:	The model may not follow the video input accurately.
Verified to have met prescribed NVIDIA quality standards:	Yes
Performance Metrics:	Quantitative and Qualitative Evaluation
Potential Known Risks:	The model's output can generate all forms of videos, including what may be considered toxic, offensive, or indecent.
Licensing:	NVIDIA Open Model License

Privacy

Field	Response
Generatable or reverse engineerable personal information?	None Known
Protected class data used to create this model?	None Known
Was consent obtained for any personal data used?	None Known
How often is dataset reviewed?	Before Release
Is there provenance for all datasets used in training?	Yes
Does data labeling (annotation, metadata) comply with privacy laws?	Yes

Safety

Field	Response
Model Application(s):	World Generation
Describe the life critical impact (if present).	None Known
Use Case Restrictions:	NVIDIA Open Model License
Model and dataset restrictions:	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.