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Parameter descriptions:

Base Model Data
Are datasources for training the base model comprehensively documented and 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 end user interacts with comprehensively documented and 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 end user interacts with made freely available?
Training Code
Is the source code of dataset processing, model training and tuning comprehensively 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 available in standardized format that provides comprehensive insight on model architecture, training, fine-tuning, and evaluation?
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?

ModelScopeT2V

by Tongyi Lab

Video-generation model based on Stable Diffusion.
Video
Limited
https://modelscope.cn/models/iic/text-to-video-synthesis/summary
Stable Diffusion (version unknown)
ModelScopeT2V-V1.5
CC-BY-NC-ND
Tonyi Lab, a lab under Alibaba.
https://careers-tongyi.alibaba.com/home
February 2023
Availability
Base Model Data
Originally trained on LAION-5B, which is ostensibly open. In general the language used is not very clear, however.
https://arxiv.org/abs/2210.08402
End User Model Data
Trained on LAION-5B, WebVid, and MSR-VTT. Unclear what data was used to train V1.5.
https://arxiv.org/pdf/2308.06571
Base Model Weights
Available through HuggingFace, however requires providing contact information and agreeing to a license agreement. Version is also unknown.
https://huggingface.co/stabilityai/stable-diffusion-3.5-large
End User Model Weights
Model made available through ModelScope.
https://modelscope.cn/models/iic/text-to-video-synthesis/summary
Training Code
Code made available on GitHub.
https://github.com/ali-vilab/VGen
Documentation
Code Documentation
Repo thoroughly documented.
https://github.com/ali-vilab/VGen
Hardware Architecture
Training setup disclosed in paper, config published on GitHub.
https://arxiv.org/pdf/2308.06571https://github.com/ali-vilab/VGen/blob/main/configs/t2v_train.yaml
Preprint
Preprint available on arXiv.
https://arxiv.org/pdf/2308.06571
Paper
No peer-reviewed paper found.
Modelcard
Model card primarily contain information about inference, with some description of training data.
https://modelscope.cn/models/iic/text-to-video-synthesis/summary
Datasheet
No datasheet found.
Access
Package
No package found.
API and Meta Prompts
No API found.
Licenses
CC-BY-NC-ND
https://modelscope.cn/models/iic/text-to-video-synthesis/summary
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