Instructions to use Yanni016/RoSSalina with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yanni016/RoSSalina with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Tongyi-MAI/Z-Image-Turbo", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Yanni016/RoSSalina") prompt = "-" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Ro$$alina

- Prompt
- -

- Prompt
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Model description
Here are some models with different numbers of training steps. The example images were made using the 4750 model
The entire training dataset was synthetic. NanaBanana Pro and Seedream 4.5 were used for generation
Trigger words
You should use Ro$$alina to trigger the image generation.
Download model
Download them in the Files & versions tab.
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Model tree for Yanni016/RoSSalina
Base model
Tongyi-MAI/Z-Image-Turbo