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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?

Step-Video

by StepFun

Chinese video generation model by SkyReels.
Video
Limited
https://huggingface.co/stepfun-ai/stepvideo-ti2v
StepVideo-T2V
StepVideo-TI2V
MIT License
StepFun, a Chinese AI company.
https://www.stepfun.com/
February 2025
Availability
Training Code
Github available, however does not contain training code.
https://github.com/stepfun-ai/Step-Video-TI2Vhttps://github.com/stepfun-ai/Step-Video-T2V
Base Model Data
No dataset found.
End User Model Data
No dataset found.
Base Model Weights
Weights made available through HuggingFace.
https://huggingface.co/stepfun-ai/stepvideo-t2v
End User Model Weights
Weights made available through HuggingFace.
https://huggingface.co/stepfun-ai/stepvideo-ti2v
Documentation
Code Documentation
No training code, so no documentation.
Hardware Architecture
Detailed hardware architecture information provided in paper.
https://arxiv.org/pdf/2502.10248
Preprint
Preprints made available through arXiv.
https://arxiv.org/pdf/2502.10248https://arxiv.org/pdf/2503.11251
Paper
No paper found.
Modelcard
Model card contains minimal information.
https://huggingface.co/stepfun-ai/stepvideo-ti2v
Datasheet
No datasheet found.
Access
Package
ComfyUI workflow for model available.
https://github.com/stepfun-ai/ComfyUI-StepVideo
API and Meta Prompts
Web interface available, accessible only when signing up.
https://yuewen.cn/videos
Licenses
MIT License, an OSI-approved license.
https://github.com/stepfun-ai/Step-Video-TI2V/blob/main/LICENSE
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