Instructions to use UDCAI/Z-Image-Fun-Distill-ComfyUI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use UDCAI/Z-Image-Fun-Distill-ComfyUI 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", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("UDCAI/Z-Image-Fun-Distill-ComfyUI") prompt = "A realistic photo of a young woman with short black hair and vibrant pink tips, wearing a metallic spiked headband and a matching spiked choker. She has large, expressive red eyes and is depicted with a slightly surprised or breathless expression, her mouth parted. She is dressed in a black and white cheerleader uniform, including a cropped tank top with a bold graphic print that says \"PHAETHON\" and a pleated mini-skirt. She is posing with her hands holding yellow pom-poms. Her skin is glistening with droplets of sweat or water, and there are floating water bubbles around her. Attached to her backside is a large, dark grey shark-like tail fin decorated with white graffiti. The background shows a sunlit athletic stadium with a running track under a clear blue sky. The overall style is high-detail with vibrant colors and dynamic lighting." image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 5e33e68d38288879a9deda1642030157fa14c9f534c548a9af4043ec92a72b3b
- Size of remote file:
- 10.8 MB
- SHA256:
- 43dee4ed315f04afecbdf9f6ccd64b3f26a49ddf82c09d0a46eb36055777f02b
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