
Fan Benefits: Click the avatar in the upper right corner - Invitation Code, enter the invitation code rh-v0990 to claim 1000 RH Coins; log in daily to claim an additional 100 RH Coins.
If not credited automatically, please bind/activate the invitation code in the upper right corner by entering rh-v0990 to claim.
Local decoding is no longer supported on the domestic site. For local decoding, please visit the overseas site:
Registration Link: Overseas RH (Decoding test workflow, requires proxy):
https://www.RunningHub.ai/user-center/1936823199386537986/webapp/?inviteCode=rh-v0990
Welcome to use Tutu's 8D Aurora Black Silk Z-Image workflow.
This workflow has been bound with "Tutu Haisi Image Generation - Z-Image-Turbo (8D Black Aurora Glossy Black Silk Long Stockings / Over-the-knee Socks)" LoRA. Open it to test the model effect online. This model is an experimental version where I ported the Haisi direction into the Z-Image-Turbo workflow, mainly used to enhance the material expression of 8D black aurora glossy silk stockings, black long stockings, and black over-the-knee socks in Z-Image-Turbo generations.
This model was annotated using Tutu Annotator, combined with Banana 2 / Banana Pro auxiliary annotation, and cleaned using Tutu's smart subject filtering feature. Training was completed using Tutu Trainer and the Tutu training workflow.
Tutu Annotator is an AI-driven image and video annotation tool optimized specifically for model training annotation. It can batch-generate high-quality training datasets and quickly reverse-engineer image and video prompts.
Tutu Trainer is a free LoRA training tool that supports model training, dataset management, model resource management, parameter presets, training checks, and pre-release organization. Its goal is to allow creators to train high-quality LoRA faster and more stably without repeatedly struggling with environments and parameters.
Official Website: https://zhaotutu.xyz/
Tutu Trainer: https://zhaotutu.xyz/downloads/tututrainer/
Tutu Annotator: https://zhaotutu.xyz/downloads/tutuannotator/
Bilibili: https://space.bilibili.com/431046154
YouTube: https://www.youtube.com/@zhaotutu/videos
X: https://x.com/bigpox12
Telegram: https://t.me/zhaotutu
TikTok: https://www.tiktok.com/@zhaotututu
GitHub: https://github.com/zhaotututu
Email: bigpox12@gmail.com
QQ: 331506796
Recommended Usage
It is recommended to start testing the LoRA weight around 0.7.
If the effect is too weak, you can moderately increase the weight; if the material is too strong or affects other parts of the image, prioritize lowering the LoRA weight rather than stacking too many negative prompts from the beginning.
It is recommended to explicitly write elements such as black long stockings / black over-the-knee socks / aurora glossy black silk in the prompt. To further enhance model features, you can add the trigger word tutujiguanghaisiv1.
Tutu's Aurora 8D HiSilk Z Image workflow
Fan Benefits: Click the avatar in the upper right corner - Invitation Code, enter the invitation code rh-v0990 to claim 1000 RH Coins; log in daily to claim an additional 100 RH Coins.
If not credited automatically, please bind/activate the invitation code in the upper right corner by entering rh-v0990 to claim.
Local decoding is no longer supported on the domestic site. For local decoding, please visit the overseas site:
Registration Link: Overseas RH (Decoding test workflow, requires proxy):
https://www.RunningHub.ai/user-center/1936823199386537986/webapp/?inviteCode=rh-v0990
Welcome to use Tutu's 8D Aurora Black Silk Z-Image workflow.
This workflow has been bound with "Tutu Haisi Image Generation - Z-Image-Turbo (8D Black Aurora Glossy Black Silk Long Stockings / Over-the-knee Socks)" LoRA. Open it to test the model effect online. This model is an experimental version where I ported the Haisi direction into the Z-Image-Turbo workflow, mainly used to enhance the material expression of 8D black aurora glossy silk stockings, black long stockings, and black over-the-knee socks in Z-Image-Turbo generations.
This model was annotated using Tutu Annotator, combined with Banana 2 / Banana Pro auxiliary annotation, and cleaned using Tutu's smart subject filtering feature. Training was completed using Tutu Trainer and the Tutu training workflow.
Tutu Annotator is an AI-driven image and video annotation tool optimized specifically for model training annotation. It can batch-generate high-quality training datasets and quickly reverse-engineer image and video prompts.
Tutu Trainer is a free LoRA training tool that supports model training, dataset management, model resource management, parameter presets, training checks, and pre-release organization. Its goal is to allow creators to train high-quality LoRA faster and more stably without repeatedly struggling with environments and parameters.
Official Website: https://zhaotutu.xyz/
Tutu Trainer: https://zhaotutu.xyz/downloads/tututrainer/
Tutu Annotator: https://zhaotutu.xyz/downloads/tutuannotator/
Bilibili: https://space.bilibili.com/431046154
YouTube: https://www.youtube.com/@zhaotutu/videos
X: https://x.com/bigpox12
Telegram: https://t.me/zhaotutu
TikTok: https://www.tiktok.com/@zhaotututu
GitHub: https://github.com/zhaotututu
Email: bigpox12@gmail.com
QQ: 331506796
Recommended Usage
It is recommended to start testing the LoRA weight around 0.7.
If the effect is too weak, you can moderately increase the weight; if the material is too strong or affects other parts of the image, prioritize lowering the LoRA weight rather than stacking too many negative prompts from the beginning.
It is recommended to explicitly write elements such as black long stockings / black over-the-knee socks / aurora glossy black silk in the prompt. To further enhance model features, you can add the trigger word tutujiguanghaisiv1.
Fan Benefits: Click the avatar in the upper right corner - Invitation Code, enter the invitation code rh-v0990 to claim 1000 RH Coins; log in daily to claim an additional 100 RH Coins.
If not credited automatically, please bind/activate the invitation code in the upper right corner by entering rh-v0990 to claim.
Local decoding is no longer supported on the domestic site. For local decoding, please visit the overseas site:
Registration Link: Overseas RH (Decoding test workflow, requires proxy):
https://www.RunningHub.ai/user-center/1936823199386537986/webapp/?inviteCode=rh-v0990
Welcome to use Tutu's 8D Aurora Black Silk Z-Image workflow.
This workflow has been bound with "Tutu Haisi Image Generation - Z-Image-Turbo (8D Black Aurora Glossy Black Silk Long Stockings / Over-the-knee Socks)" LoRA. Open it to test the model effect online. This model is an experimental version where I ported the Haisi direction into the Z-Image-Turbo workflow, mainly used to enhance the material expression of 8D black aurora glossy silk stockings, black long stockings, and black over-the-knee socks in Z-Image-Turbo generations.
This model was annotated using Tutu Annotator, combined with Banana 2 / Banana Pro auxiliary annotation, and cleaned using Tutu's smart subject filtering feature. Training was completed using Tutu Trainer and the Tutu training workflow.
Tutu Annotator is an AI-driven image and video annotation tool optimized specifically for model training annotation. It can batch-generate high-quality training datasets and quickly reverse-engineer image and video prompts.
Tutu Trainer is a free LoRA training tool that supports model training, dataset management, model resource management, parameter presets, training checks, and pre-release organization. Its goal is to allow creators to train high-quality LoRA faster and more stably without repeatedly struggling with environments and parameters.
Official Website: https://zhaotutu.xyz/
Tutu Trainer: https://zhaotutu.xyz/downloads/tututrainer/
Tutu Annotator: https://zhaotutu.xyz/downloads/tutuannotator/
Bilibili: https://space.bilibili.com/431046154
YouTube: https://www.youtube.com/@zhaotutu/videos
X: https://x.com/bigpox12
Telegram: https://t.me/zhaotutu
TikTok: https://www.tiktok.com/@zhaotututu
GitHub: https://github.com/zhaotututu
Email: bigpox12@gmail.com
QQ: 331506796
Recommended Usage
It is recommended to start testing the LoRA weight around 0.7.
If the effect is too weak, you can moderately increase the weight; if the material is too strong or affects other parts of the image, prioritize lowering the LoRA weight rather than stacking too many negative prompts from the beginning.
It is recommended to explicitly write elements such as black long stockings / black over-the-knee socks / aurora glossy black silk in the prompt. To further enhance model features, you can add the trigger word tutujiguanghaisiv1.
