Instructions to use 9r4n4y/Z-Image-Turbo-Ghibli-Style-backup with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use 9r4n4y/Z-Image-Turbo-Ghibli-Style-backup 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("9r4n4y/Z-Image-Turbo-Ghibli-Style-backup") prompt = "an image of a young woman sitting outdoors on grass. She appears to be in her 20s with brown hair tied back in a ponytail. She is wearing a dark blue sports bra-style crop top that shows her midriff, paired with high-waisted olive green cargo pants. She has a white shirt or jacket draped over her shoulders. Around her neck is a silver chain necklace, and she is wearing small hoop earrings. " image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- a9d47f4e1033ae5a3388311422e8bed8df68f80d1136b15655010535c5a55cd7
- Size of remote file:
- 1.27 MB
- SHA256:
- 5bf09af5a968f4420d75611992f963c7a41dc1d997925669be2c4139fb9e6686
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