Instructions to use minimaxir/sdxl-wrong-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use minimaxir/sdxl-wrong-lora with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("minimaxir/sdxl-wrong-lora") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
safetensors note
Browse files
README.md
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A LoRA for SDXL 1.0 Base which improves output image quality after loading it and using `wrong` as a negative prompt during inference. You can demo image generation using this LoRA in [this Colab Notebook](https://colab.research.google.com/github/minimaxir/sdxl-experiments/blob/main/sdxl_image_generation.ipynb).
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Benefits of using this LoRA:
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- Higher detail in textures/fabrics, particularly at full 1024x1024 resolution.
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A LoRA for SDXL 1.0 Base which improves output image quality after loading it and using `wrong` as a negative prompt during inference. You can demo image generation using this LoRA in [this Colab Notebook](https://colab.research.google.com/github/minimaxir/sdxl-experiments/blob/main/sdxl_image_generation.ipynb).
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The LoRA is also available in a `safetensors` format for other UIs such as A1111; however this LoRA was created using `diffusers` and I cannot guarantee its efficacy outside of it.
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Benefits of using this LoRA:
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- Higher detail in textures/fabrics, particularly at full 1024x1024 resolution.
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