import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("fill-in-base-model", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("mkshing/lora-sdxl-dog")
prompt = "a sbu dog in a bucket"
image = pipe(prompt).images[0]base_model: stable-diffusion-xl-base-1.0 instance_prompt: a sbu dog license: openrail++
SDXL LoRA DreamBooth - mkshing/lora-sdxl-dog
- Prompt
- a sbu dog in a bucket
- Prompt
- a sbu dog in a bucket
- Prompt
- a sbu dog in a bucket
- Prompt
- a sbu dog in a bucket
Model description
These are mkshing/lora-sdxl-dog LoRA adaption weights for /fsx/proj-jp-stable-diffusion/models/stable-diffusion/stable-diffusion-xl-base-1.0. The weights were trained using DreamBooth. LoRA for the text encoder was enabled: False. Special VAE used for training: None.
Trigger words
You should use a sbu dog to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
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