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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?

Wan

by Alibaba Cloud

Video-generation model by Alibaba Cloud.
Video
Full
https://huggingface.co/Wan-AI/Wan2.1-T2V-14B
Wan2.1-T2V-14B
Wan2.1-T2V-14B
Apache-2.0
Alibaba Cloud, a subdivision of the Chinese multinational technology company Alibaba.
https://www.alibabacloud.com/
February 2025
Availability
Training Code
Repository exists however does not contain training code.
https://github.com/Wan-Video/Wan2.1
Base Model Data
No explicit description of data sources found.
End User Model Data
No explicit description of data sources found.
Base Model Weights
Weights made available on HuggingFace.
https://huggingface.co/Wan-AI/Wan2.1-T2V-14B
End User Model Weights
Weights made available on HuggingFace.
https://huggingface.co/Wan-AI/Wan2.1-T2V-14B
Documentation
Code Documentation
No training code, so no documentation.
Hardware Architecture
No hardware information found.
Preprint
No preprint found. Model card mentions it is forthcoming.
Paper
No paper found.
Modelcard
Model card primarily contains information regarding usage and architecture, little information regarding training and fine-tuning.
https://huggingface.co/Wan-AI/Wan2.1-T2V-14B
Datasheet
No datasheet found.
Access
Package
ComfyUI workflow for model available.
https://github.com/kijai/ComfyUI-WanVideoWrapper
API and Meta Prompts
Model available through HuggingFace space.
https://huggingface.co/spaces/Wan-AI/Wan2.1
Licenses
Model licensed through Apache-2.0, an OSI-approved license.
https://huggingface.co/Wan-AI/Wan2.1-T2V-14B#license-agreement
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