Instructions to use Burroughs352/CS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Burroughs352/CS 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("Burroughs352/CS") prompt = "laire is standing on a footpath in a suburban setting. She is staring at the viewer and smiling. She has long brown hair. She is wearing a purple t-shirt and blue jeans. It is night time. The scene is illuminated by the moon shining between the trees. There are lots of trees. Roots are showing through the ground. " image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
CS

- Prompt
- laire is standing on a footpath in a suburban setting. She is staring at the viewer and smiling. She has long brown hair. She is wearing a purple t-shirt and blue jeans. It is night time. The scene is illuminated by the moon shining between the trees. There are lots of trees. Roots are showing through the ground.
Model description
CS Z Image Turbo V4.3
Trigger words
You should use Claire to trigger the image generation.
Download model
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Model tree for Burroughs352/CS
Base model
Tongyi-MAI/Z-Image-Turbo