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metadata
license: other
language:
  - en
pipeline_tag: text-to-image
tags:
  - flux
  - flux.1
  - flux.1-schnell
  - flux.1-dev
  - flux-merge
  - merge
  - blocks
  - finetune
  - block patcher
library_name: diffusers

Brief introduction:

Also on CivitAI

可能是目前快速出图(10步以内)版 Flux 模型中,出图质量最好、细节最丰富的基础模型。

May be the Best Quality Step 6-10 Model, In some details, it surpasses the Flux.1 Dev model and approaches the Flux.1 Pro model.

Based on Flux-Fusion-V2, Merge of flux-dev-de-distill, finetuned by ComfyUI, Block_Patcher_ComfyUI, ComfyUI_essentials and other tools. Recommended 6-10 steps. Greatly improved quality compared to other Flux.1 model.



Recommend:

UNET versions (Model only) need Text Encoders and VAE, I recommend use below CLIP and Text Encoder model, will get better prompt guidance:

**Simple workflow ** very simple workflow as below, needn't any other comfy custom nodes:


Thanks for:

https://huggingface.co/Anibaaal, Flux-Fusion is a very good mix and tuned model.

https://huggingface.co/nyanko7, Flux-dev-de-distill is a great experimental project! thanks for the inference.py scripts.

https://huggingface.co/MonsterMMORPG, Furkan share a lot of Flux.1 model testing and tuning courses, some special test for the de-distill model.

https://github.com/cubiq/Block_Patcher_ComfyUI, cubiq's Flux blocks patcher sampler let me do a lot of test to know how the Flux.1 block parameter value change the image gerentrating. His ComfyUI_essentials have a FluxBlocksBuster node, let me can adjust the blocks value easy. that is a great work!

https://huggingface.co/twodgirl, Share the model quantization script and the test dataset.

https://huggingface.co/John6666, Share the model convert script and the model collections.


LICENSE

The weights fall under the FLUX.1 [dev] Non-Commercial License.