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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?

Openjourney

by Prompthero

Model trained on MidJourney images.
Image
Full
https://openjourney.art
Stable-Diffusion-v1.5
OpenJourney-v4
creativeml-openrail-m
Prompt engineering site.
https://prompthero.com/
November 2022
Availability
Training Code
No training code found.
Base Model Data
Originally trained on LAION-5B, which is ostensibly open.
https://arxiv.org/abs/2210.08402
End User Model Data
Model card mentions the model was fine-tuned on Midjourney images however no link is provided. Given that the model creators also own a Midjourney image database it can be assumed the model was fine-tuned on these images.
https://huggingface.co/prompthero/openjourney
Base Model Weights
Model not made publicly available.
End User Model Weights
Weights are provided as a safetensors file.
https://huggingface.co/prompthero/openjourney/tree/main
Documentation
Code Documentation
No training code found, so no documentation.
Hardware Architecture
No detailed architecture information provided.
Preprint
No preprint found.
Paper
No paper found.
Modelcard
Model card only contains minimal information.
Datasheet
No data published, so no data sheet.
Access
Package
No package found.
API and Meta Prompts
Inference API available through HuggingFace.
https://huggingface.co/prompthero/openjourney-v4
Licenses
Creativeml-OpenRail-M, not an OSI-approved license.
https://huggingface.co/prompthero/openjourney-v4
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