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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?

CogVideoX

by Zhipu AI (Z.ai)

text-to-video generation model by QingYing
Video
Full
https://huggingface.co/zai-org/CogVideoX-5b
CogVideoX-5b
CogVideoX1.5-5B
Apache-2.0
Zhipu AI, branded as Z.ai, is a Chinese technology company specializing in artificial intelligence.
https://www.zhipuai.cn/en/
August 2024
Availability
Base Model Data
They use CogView which has closed dataset along other datasets.
https://arxiv.org/abs/2205.15868
End User Model Data
https://arxiv.org/abs/2205.15868
Base Model Weights
Weights are available on HuggingFace.
https://huggingface.co/zai-org/CogVideoX-2b
End User Model Weights
Weights are available on HuggingFace.
https://huggingface.co/zai-org/CogVideoX1.5-5B
Training Code
https://github.com/zai-org/CogVideo?tab=readme-ov-file
Documentation
Code Documentation
https://huggingface.co/zai-org/CogVideoX1.5-5B
Hardware Architecture
Explained in the paper.
https://arxiv.org/abs/2205.15868
Preprint
Newest paper on their newest model.
https://openreview.net/forum?id=LQzN6TRFg9
Paper
Presented in ICLR in 2023.
https://iclr.cc/virtual/2023/poster/11213
Modelcard
https://huggingface.co/zai-org/CogVideoX1.5-5B
Datasheet
Access
Package
API and Meta Prompts
https://huggingface.co/spaces/zai-org/CogVideoX-5B-Space
Licenses
Model licensed under Apache-2.0, an OSI-approved license.
https://huggingface.co/zai-org/CogVideoX1.5-5B#model-license
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