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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?

Mochi

by Genmo

Open-source video generation model
Video
Full
https://huggingface.co/genmo/mochi-1-preview
Mochi-1-Preview
Mochi-1-Preview
Apache-2.0
Genmo, a Silicon-valley-based AI lab.
https://www.genmo.ai/
October 2024
Availability
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/genmo/mochi-1-preview
End User Model Weights
Weights made available on HuggingFace.
https://huggingface.co/genmo/mochi-1-preview
Training Code
Repository exists however does not contain training code.
https://github.com/genmoai/mochi
Documentation
Code Documentation
No training code, so no documentation.
Hardware Architecture
No hardware information found.
Preprint
No preprint found.
Paper
No paper found.
Modelcard
Model card primarily contains information regarding usage and architecture, little information regarding training and fine-tuning.
https://huggingface.co/genmo/mochi-1-preview
Datasheet
No datasheet found.
Access
Package
ComfyUI workflow for model available.
https://github.com/kijai/ComfyUI-MochiWrapper
API and Meta Prompts
Inference api available
https://huggingface.co/genmo/mochi-1-preview
Licenses
Model licensed through Apache-2.0, an OSI-approved license.
https://huggingface.co/genmo/mochi-1-preview
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