
Fan benefits: Click on the top right avatar Invitation Code, enter the invitation code rh v0990 to receive 1000 RH coins; log in daily to receive 100 RH coins.
If it does not automatically credit, please bind/activate the invitation code in the top right corner, fill in rh v0990 to claim.
The domestic site no longer supports local decoding. For local decoding, please visit the overseas site:
Registration link: Overseas version RH (Decoding test workflow, requires VPN):
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 is already bound with "Tutu High Silk Creation Z Image Turbo (8D Black Aurora Glossy Black Silk Thigh-High Socks / Over-the-Knee Socks)" LoRA. Open it to test the model effects online. This model is an experimental version where I migrated the high silk direction into the Z Image Turbo workflow, mainly used to enhance the material representation of 8D black aurora glossy silk stockings, black thigh-high socks, and black over-the-knee socks in Z Image Turbo outputs.
This model uses the Tutu Annotator for material annotation, combined with Banana 2 / Banana Pro for auxiliary annotation, and then cleans tags using Tutu's intelligent subject filtering function. Training is completed using Tutu Trainer and Tutu Training Workflow.
Tutu Annotator is an AI-driven image and video annotation tool, optimized for model training annotations. It can batch generate high-quality training datasets and quickly reverse-engineer prompts for images and videos.
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 enable creators to train high-quality LoRA faster and more stably without repeatedly tweaking 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 LoRA weights from around 0.7.
If the effect is too weak, you can appropriately increase the weight; if the material is too strong or affects other parts of the image, prioritize reducing the LoRA weight instead of piling up many negative prompts from the beginning.
In the prompts, it is recommended to explicitly include elements such as black thigh-high socks / black over-the-knee socks / aurora glossy black silk. If you want to further enhance the model features, you can add the trigger word tutujiguanghaisiv1.
Fan benefits: Click on the top right avatar Invitation Code, enter the invitation code rh v0990 to receive 1000 RH coins; log in daily to receive 100 RH coins.
If it does not automatically credit, please bind/activate the invitation code in the top right corner, fill in rh v0990 to claim.
The domestic site no longer supports local decoding. For local decoding, please visit the overseas site:
Registration link: Overseas version RH (Decoding test workflow, requires VPN):
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 is already bound with "Tutu High Silk Creation Z Image Turbo (8D Black Aurora Glossy Black Silk Thigh-High Socks / Over-the-Knee Socks)" LoRA. Open it to test the model effects online. This model is an experimental version where I migrated the high silk direction into the Z Image Turbo workflow, mainly used to enhance the material representation of 8D black aurora glossy silk stockings, black thigh-high socks, and black over-the-knee socks in Z Image Turbo outputs.
This model uses the Tutu Annotator for material annotation, combined with Banana 2 / Banana Pro for auxiliary annotation, and then cleans tags using Tutu's intelligent subject filtering function. Training is completed using Tutu Trainer and Tutu Training Workflow.
Tutu Annotator is an AI-driven image and video annotation tool, optimized for model training annotations. It can batch generate high-quality training datasets and quickly reverse-engineer prompts for images and videos.
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 enable creators to train high-quality LoRA faster and more stably without repeatedly tweaking 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 LoRA weights from around 0.7.
If the effect is too weak, you can appropriately increase the weight; if the material is too strong or affects other parts of the image, prioritize reducing the LoRA weight instead of piling up many negative prompts from the beginning.
In the prompts, it is recommended to explicitly include elements such as black thigh-high socks / black over-the-knee socks / aurora glossy black silk. If you want to further enhance the model features, you can add the trigger word tutujiguanghaisiv1.