









pipi-moss-photorealistic01
Model Information
Like and bookmark this model to use it. See below for generation instructions
Trigger word: None, Weight: 0.5-1, Best weight: 0.8;
Sampling method: Euler; Sampling steps: 30; CFG scale: 2.5;
Better results when paired with the krea official base model
Chinese Station
moss text-to-image online generation address: https://www.RunningHub.cn/post/2117031573169197057
International Station
moss text-to-image online generation address: https://www.RunningHub.ai/zh-cn/post/2117033448628531201
Fan perk: Register to get 1000 points, log in daily for 100 points, play with RTX 4090! Experience the ultimate power of 48G!
Domestic website: https://www.RunningHub.cn/?inviteCode=cn-v1036
International website: https://www.RunningHub.ai/?inviteCode=rh-v1104
QQ Communication Group: 775425105
This model is tagged using Tutu's Super Intelligent Tagger and trained using Tutu's Super Trainer. The trainer is super convenient, zero-threshold to start, fully model-supported, out-of-the-box, zero environment dependencies, zero parameter configuration, graphical interface, and rich in resources. Friends interested in model training and prompt reverse-engineering are welcome to try it. Download address: zhaotutu.xyz
Like and bookmark this model to use it. See below for generation instructions
Trigger word: None, Weight: 0.5-1, Best weight: 0.8;
Sampling method: Euler; Sampling steps: 30; CFG scale: 2.5;
Better results when paired with the krea official base model
Chinese Station
moss text-to-image online generation address: https://www.RunningHub.cn/post/2117031573169197057
International Station
moss text-to-image online generation address: https://www.RunningHub.ai/zh-cn/post/2117033448628531201
Fan perk: Register to get 1000 points, log in daily for 100 points, play with RTX 4090! Experience the ultimate power of 48G!
Domestic website: https://www.RunningHub.cn/?inviteCode=cn-v1036
International website: https://www.RunningHub.ai/?inviteCode=rh-v1104
QQ Communication Group: 775425105
This model is tagged using Tutu's Super Intelligent Tagger and trained using Tutu's Super Trainer. The trainer is super convenient, zero-threshold to start, fully model-supported, out-of-the-box, zero environment dependencies, zero parameter configuration, graphical interface, and rich in resources. Friends interested in model training and prompt reverse-engineering are welcome to try it. Download address: zhaotutu.xyz
