RedCraft | 红潮 CADS Commercial & Advertising Design System

RED.2 BF16 (ArtAug)
METAFILM_Ai
9 months ago

RedCraft-红潮 12B-METAFILM

基于 artificialanalysis.ai -Text to Image Arena 擂台赛 精选作品集

元影智能工作室 by AiARTiST

可能是目前快速出图(10步以内)版 BF16 模型中,出图质量较好、细节较丰富的基础模型。

Fine Quality Steps 10-20 Model, In some details, it surpasses the Flux series models and approaches the 20B Parameters models.

境内已发布在 Modelscope 魔搭社区,感受极速下载!

RedCraft | 红潮 CADS Commercial & Advertising Design System · 模型库

Also on Huggingface.co soon

Based on METAFILM AI - Commercial & Advertising Design System, Merge of flux-dev-de-distill, finetuned by ComfyUI, Block_Patcher_ComfyUI, ComfyUI_essentials and other tools. Recommended 10-20 steps. Greatly improved quality compared to other 12B models.

基于

De-Distill & CADS商业素材 FP16

支持在线生成 ComfyUI WebUI

10-20 STEPS Euler / DPM++2M | beta / SGM_Uniform

CFG 3-3.5

Real CFG needs to be set (ignore guidance, or set to 0)

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未蒸馏PRO版本 将在测试完成后公开

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同样推荐选择大杨老师的 8bit finetune 版本:

Flux1-DedistilledMixTuned-V1 - v1.0 fp8 | Flux Checkpoint | Civitai

可能是目前能找到最符合官方基准风格并且出图效果最好的加速模型

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: a very simple workflow as below, needn't any other comfy custom nodes(For GGUF version, please use UNET Loader(GGUF) node of city96's):


Thanks for:

https://huggingface.co/wikeeyang, Wikee Yang for carefully finetune the 8-bit model and providing the model informations,You can find it here:

wikeeyang/Flux.1-Dedistilled-Mix-Tuned-fp8 · Hugging Face

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.

https://github.com/city96/ComfyUI-GGUF, Native support GGUF Quantization Model.

https://github.com/leejet/stable-diffusion.cpp, Provider pure C/C++ GGUF model convert scripts.

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测试问题请留言,业务合作看个人首页 +V Zyuan980

做好工具人 服务艺术家 更多资料:https://x1f3ewlrcf.feishu.cn/wiki/BjJ1waQaLitPB4k7Lbvc0MaVnzb?fromScene=spaceOverview&open_tab_from=wiki_home

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What is RedCraft | 红潮 CADS Commercial & Advertising Design System?

RedCraft | 红潮 CADS Commercial & Advertising Design System is a highly specialized Image generation AI Model of type Safetensors / Checkpoint AI Model created by AI community user METAFILM_Ai. Derived from the powerful Stable Diffusion (SDXL 1.0) model, RedCraft | 红潮 CADS Commercial & Advertising Design System has undergone an extensive fine-tuning process, leveraging the power of a dataset consisting of images generated by other AI models or user-contributed data. This fine-tuning process ensures that RedCraft | 红潮 CADS Commercial & Advertising Design System is capable of generating images that are highly relevant to the specific use-cases it was designed for, such as photorealistic, base model, artistic.

With a rating of 0 and over 0 ratings, RedCraft | 红潮 CADS Commercial & Advertising Design System is a popular choice among users for generating high-quality images from text prompts.

Can I download RedCraft | 红潮 CADS Commercial & Advertising Design System?

Yes! You can download the latest version of RedCraft | 红潮 CADS Commercial & Advertising Design System from here.

How to use RedCraft | 红潮 CADS Commercial & Advertising Design System?

To use RedCraft | 红潮 CADS Commercial & Advertising Design System, download the model checkpoint file and set up an UI for running Stable Diffusion models (for example, AUTOMATIC1111). Then, provide the model with a detailed text prompt to generate an image. Experiment with different prompts and settings to achieve the desired results. If this sounds a bit complicated, check out our initial guide to Stable Diffusion – it might be of help. And if you really want to dive deep into AI image generation and understand how set up AUTOMATIC1111 to use Safetensors / Checkpoint AI Models like RedCraft | 红潮 CADS Commercial & Advertising Design System, check out our crash course in AI image generation.

Download (1.22 MB) Download available on desktop only
You'll need to use a program like A1111 to run this – learn how in our crash course

Popularity

770 ~10

Info

Base model: Flux.1 D

Version RED.2 BF16 (ArtAug): 1 File

To download these files, please visit this page from a desktop computer.

About this version: RED.2 BF16 (ArtAug)

RED.2 美学评估基于 DiffSynth-Studio 生成理解交互训练项目 ArtAug

The training process of ArtAug consists of the following steps:

  1. Synthesis-Understanding Interaction: After generating an image using the image generation model, we employ a multimodal large language model (Qwen2-VL-72B) to analyze the image content and provide suggestions for modifications, which then lead to the regeneration of a higher quality image.

  2. Data Generation and Filtering: Interactive generation involves long inference times and sometimes produce poor image content. Therefore, we generate a large batch of image pairs offline, filter them, and use them for subsequent training.

  3. Differential Training: We apply differential training techniques to train a LoRA model, enabling it to learn the differences between images before and after enhancement, rather than directly training on the dataset of enhanced images.

  4. Iterative Enhancement: The trained LoRA model is fused into the base model, and the entire process is repeated multiple times with the fused model until the interaction algorithm no longer provides significant enhancements. The LoRA models produced in each iteration are combined to produce this final model.

This model integrates the aesthetic understanding of Qwen2-VL-72B into FLUX.1[dev], leading to an improvement in the quality of generated images.

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