Instructions to use mkshing/lora-trained-jsdxl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mkshing/lora-trained-jsdxl 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/japanese-stable-diffusion-xl", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("mkshing/lora-trained-jsdxl") prompt = "輻の犬" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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license:
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base_model: stabilityai/japanese-stable-diffusion-xl
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instance_prompt: 輻の犬
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tags:
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- japanese-stable-diffusion-xl
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- japanese-stable-diffusion-xl-diffusers
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- text-to-image
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- diffusers
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- lora
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license: other
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base_model: stabilityai/japanese-stable-diffusion-xl
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instance_prompt: 輻の犬
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tags:
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- japanese-stable-diffusion
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- japanese-stable-diffusion-xl
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- text-to-image
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- diffusers
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- lora
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