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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?

OmniGen

by Beijing Academy of Artificial Intelligence

Model designed to generate images from multimodal prompts.
Image
Full
https://huggingface.co/Shitao/OmniGen-v1
OmniGen-v1
OmniGen-v1
MIT License
Chinese non-profit AI lab.
https://www.baai.ac.cn/en/
October 2024
Availability
Training Code
Only fine-tuning code made available on GitHub.
https://github.com/VectorSpaceLab/OmniGen
Base Model Data
Dataset made available, public datasets used to create it outlined in paper.
https://huggingface.co/collections/yzwang/x2i-dataset-674c66d1d700f7f816a9590dhttps://arxiv.org/pdf/2409.11340
End User Model Data
Base Model Weights
Weights made available on HuggingFace.
https://huggingface.co/Shitao/OmniGen-v1
End User Model Weights
Documentation
Code Documentation
Fine-tuning code is sparsely documented.
https://github.com/VectorSpaceLab/OmniGen
Hardware Architecture
Training setup is sparsely documented.
https://arxiv.org/pdf/2409.11340
Preprint
preprint made available on arXiv.
https://arxiv.org/pdf/2409.11340
Paper
Modelcard
Model card provides information about inference and fine-tuning, but not model architecture or training.
https://huggingface.co/Shitao/OmniGen-v1
Datasheet
Data thoroughly outlined.
https://huggingface.co/datasets/yzwang/X2I-subject-drivenhttps://huggingface.co/datasets/yzwang/X2I-text-to-imagehttps://huggingface.co/datasets/yzwang/X2I-mm-instructionhttps://huggingface.co/datasets/yzwang/X2I-in-context-learninghttps://huggingface.co/datasets/yzwang/X2I-computer-vision
Access
Package
No package found.
API and Meta Prompts
Online API available.
https://omnigenai.org/playground
Licenses
MIT license, an OSI-approved license.
https://huggingface.co/Shitao/OmniGen-v1#license
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