Instructions to use liming518/ZITflatchets with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use liming518/ZITflatchets 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("liming518/ZITflatchets") prompt = "young latino woman wearing a bikini" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Update README.md
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README.md
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- output:
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url: images/img1.jpg
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text: 'young latino woman wearing a bikini'
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base_model: Tongyi-MAI/Z-Image-Turbo
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instance_prompt: null
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- output:
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url: images/img1.jpg
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text: 'young latino woman wearing a bikini'
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- output:
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url: images/img2.jpg
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text: 'young latino woman wearing a tight top'
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base_model: Tongyi-MAI/Z-Image-Turbo
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instance_prompt: null
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