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Parameter descriptions:

Base Model Data
Are datasources for training the base model comprehensively documented and freely made available? In case a distinction between base (foundation) and end (user) model is not applicable, this mirrors the end model data entries.
End User Model Data
Are datasources for training the model that the enduser interacts with comprehensively documented and freely made available?
Base Model Weights
Are the weights of the base models made freely available? In case a distinction between base (foundation) and end (user) model is not applicable, this mirrors the end model data entries.
End User Model Weights
Are the weights of the model that the enduser interacts with made freely available?
Training Code
Is the source code of datasource processing, model training and tuining comprehensively and freely made available?
Code Documentation
Is the source code of datasource processing, model training and tuning comprehensively documented?
Hardware Architecture
Is the hardware architecture used for datasource processing and model training comprehensively documented?
Preprint
Are archived preprint(s) are available that detail all major parts of the system including datasource processing, model training and tuning steps?
Paper
Are peer-reviewed scientific publications available that detail all major parts of the system including datasource processing, model training and tuning steps?
Modelcard
Is a model card in standardized format available that provides comprehensive insight on model architecture, training, fine-tuning, and evaluation are available?
Datasheet
Is a datasheet as defined in "Datasheets for Datasets" (Gebru et al. 2021) available?
Package
Is a packaged release of the model available on a software repository (e.g. a Python Package Index, Homebrew)?
API and Meta Prompts
Is an API available that provides unrestricted access to the model (other than security and CDN restrictions)? If applicable, this entry also collects information on the use and availability of meta prompts.
Licenses
Is the project fully covered by Open Source Initiative (OSI)-approved licenses, including all data sources and training pipeline code?

Cosmos

by NVIDIA

Given a text or video input, predicts the next 120 frames.
Video
Full
https://huggingface.co/nvidia/Cosmos-1.0-Diffusion-14B-Video2World
Cosmos-1.0-Diffusion-14B-Text2World
Cosmos-1.0-Diffusion-14B-Video2World
NVIDIA Open Model License
NVIDIA, a major chip manufacturer.
https://www.nvidia.com
January 2025
Availability
Training Code
Base Model Data
We use both proprietary video datasets and publicly available open-domain Internet videos to train our models.
https://arxiv.org/pdf/2501.03575
End User Model Data
We use both proprietary video datasets and publicly available open-domain Internet videos to train our models.
https://arxiv.org/pdf/2501.03575
Base Model Weights
behind consent form
https://huggingface.co/nvidia/Cosmos-1.0-Diffusion-14B-Video2World/tree/main
End User Model Weights
behind consent form
https://huggingface.co/nvidia/Cosmos-1.0-Diffusion-14B-Video2World/tree/main
Documentation
Code Documentation
Hardware Architecture
Preprint
https://arxiv.org/abs/2501.03575
Paper
Modelcard
https://huggingface.co/nvidia/Cosmos-1.0-Diffusion-14B-Video2World
Datasheet
Access
Package
ComfyUI workflow for model available.
https://comfyanonymous.github.io/ComfyUI_examples/cosmos/
API and Meta Prompts
Licenses
weights under Nvidia Open World License and some code under Apache 2
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