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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?

FLUX.1

by Black Forest Labs

Rectified flow image-generation model.
Image
Full
https://huggingface.co/black-forest-labs/FLUX.1-dev
FLUX.1-Dev
FLUX.1-Dev
FLUX.1 [dev] Non-Commercial License
Image-generation model start-up.
https://huggingface.co/black-forest-labs
July 2024
Availability
Training Code
No training code found.
Base Model Data
No data source list found.
End User Model Data
Base Model Weights
Gated model made available through HuggingFace.
https://huggingface.co/black-forest-labs/FLUX.1-dev
End User Model Weights
Gated model made available through HuggingFace.
https://huggingface.co/black-forest-labs/FLUX.1-dev
Documentation
Code Documentation
No training code, so not documented.
Hardware Architecture
No hardware information found.
Preprint
No preprint found.
Paper
No paper found.
Modelcard
Model card primarily contains inference and license information.
https://huggingface.co/black-forest-labs/FLUX.1-dev
Datasheet
No data, so no data sheet.
Access
Package
Only package found for mac.
https://pypi.org/project/mflux/
API and Meta Prompts
Various paid APIs exist.
https://docs.bfl.ml/https://replicate.com/collections/fluxhttps://fal.ai/models/fal-ai/flux/dev
Licenses
FLUX.1 [dev] Non-Commercial License, not an OSI-approved license.
https://huggingface.co/black-forest-labs/FLUX.1-dev#license
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