https://huggingface.co/Shakker-Labs/FLUX.1-dev-ControlNet-Depth

https://huggingface.co/Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro

Text:

Emad@EMostaque

Delighted to announce the public open source release of #StableDiffusion!

Please see our release post and retweet! stability.ai/blog/stable-di...

Proud of everyone involved in releasing this tech that is the first of a series of models to activate the creative potential of humanity

11:07 AM • Aug 22, 2022

Has anyone of you stumbled upon any information on how to get it running on machines like mine, or does it just not have enough power?

Release: https://github.com/bghira/SimpleTuner/releases/tag/v0.9.8.3

Release: https://github.com/rupeshs/fastsdcpu/releases/tag/v1.0.0-beta.36

Additional Details: https://github.com/rupeshs/fastsdcpu/tree/main?tab=readme-ov-file#flux1-schnell-openvino-support

V2 is quantized in a better way and is 0.5 GB larger than the previous version.

On Hugging Face: https://huggingface.co/lllyasviel/flux1-dev-bnb-nf4

Announcement: https://github.com/lllyasviel/stable-diffusion-webui-forge/discussions/981

Among other improvements, the new defaults set --flux_guidance_value=1, removing the need to use CFG nodes at inference, reducing generation time and improving image quality of LoRAs slightly.

Changelog: https://github.com/bghira/SimpleTuner/releases/tag/v0.9.8.1

Sample LoRA: https://huggingface.co/ptx0/flux-dreambooth-lora-r16-dev-cfg1/blob/main/pytorch_lora_weights.safetensors

I think this was here a while ago, but I lost the post. If I remember, there was an extension where someone had built up a repository of poses, and then in the UI you could go through them and pick out the one you wanted for your image. Does anyone remember that? I have controlnet and can do poses, but finding them is a bear right now.

Changelog: https://github.com/mcmonkeyprojects/SwarmUI/releases/tag/0.9.2-Beta

Docs: https://github.com/mcmonkeyprojects/SwarmUI/blob/master/docs/Model%20Support.md#black-forest-labs-flux1-models

From The Hugging Face Model Card:

Not Ready

This is a WIP and not ready for use. This is an early testing version for research and development. You may know what this is and how to use it, if so, feel free, but it will change as I continue to develop it. I plan to do many updates to it frequently. So you may want to set a revision if you intend to use it anyway.

What is this?

FLUX.1-schnell is an amazing distilled model with an apache 2.0 license. However, it is not finetunable. LoRAs, IP adapters, control nets, etc, cannot be trained on it because it is distilled. The goal of this project is to finetune a non-distilled version of it that can be used as a training base to train adapters for FLUX.1-schnell.

Current Issues

Since we are breaking the distillation, this model will need many steps and guidance to produce good results. Currently, this model, like the schnell version, does not have guidance embeddings. Because of this (and possible other factors) images generated with this model will not look great. However, this hopefully will not affect training, since guidance is not used during training. The things trained on this model are intended to be used on the schnell version anyway. I am working on training guidance embeddings for it, but hopefully it will work as a training base without them.