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("asach/lora-trained-xl")
prompt = "abstract photos"
image = pipe(prompt).images[0]YAML Metadata Error:"base_model" with value "/home/ubuntu/LLM/.conda/om/sdx/stable-diffusion-xl-base-1.0" is not valid. Use a model id from https://hf.co/models.
LoRA DreamBooth - asach/lora-trained-xl
These are LoRA adaption weights for /home/ubuntu/LLM/.conda/om/sdx/stable-diffusion-xl-base-1.0. The weights were trained on abstract photos using DreamBooth. You can find some example images in the following.
LoRA for the text encoder was enabled: False.
Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.
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