LoRA DreamBooth - jbilcke-hf/sdxl-modern-pixar
These are LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0 trained on @fffiloni's SD-XL trainer. The weights were trained on the concept prompt:
modern-pixar
Use this keyword to trigger your custom model in your prompts. LoRA for the text encoder was enabled: False. Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.
Usage
Make sure to upgrade diffusers to >= 0.19.0:
pip install diffusers --upgrade
In addition make sure to install transformers, safetensors, accelerate as well as the invisible watermark:
pip install invisible_watermark transformers accelerate safetensors
To just use the base model, you can run:
import torch
from diffusers import DiffusionPipeline, AutoencoderKL
device = "cuda" if torch.cuda.is_available() else "cpu"
vae = AutoencoderKL.from_pretrained('madebyollin/sdxl-vae-fp16-fix', torch_dtype=torch.float16)
pipe = DiffusionPipeline.from_pretrained(
"stabilityai/stable-diffusion-xl-base-1.0",
vae=vae, torch_dtype=torch.float16, variant="fp16",
use_safetensors=True
)
pipe.to(device)
# This is where you load your trained weights
specific_safetensors = "pytorch_lora_weights.safetensors"
lora_scale = 0.9
pipe.load_lora_weights(
'jbilcke-hf/sdxl-modern-pixar',
weight_name = specific_safetensors,
# use_auth_token = True
)
prompt = "A majestic modern-pixar jumping from a big stone at night"
image = pipe(
prompt=prompt,
num_inference_steps=50,
cross_attention_kwargs={"scale": lora_scale}
).images[0]
- Downloads last month
- 12
Model tree for jbilcke-hf/sdxl-modern-pixar
Base model
stabilityai/stable-diffusion-xl-base-1.0
Adapter
this model