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("erikhsos/campusbier_LoRA")
prompt = "a photo of CAMPUPUSBIER beer"
image = pipe(prompt).images[0]SDXL LoRA DreamBooth - erikhsos/campusbier_LoRA
Model description
These are erikhsos/campusbier_LoRA LoRA adaption weights for stabilityai/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: madebyollin/sdxl-vae-fp16-fix.
Trigger words
You should use a photo of CAMPUPUSBIER beer to trigger the image generation.
Training Settings
!accelerate launch train_dreambooth_lora_sdxl.py
--pretrained_model_name_or_path="stabilityai/stable-diffusion-xl-base-1.0"
--pretrained_vae_model_name_or_path="madebyollin/sdxl-vae-fp16-fix"
--dataset_name="campusbiernew"
--output_dir="campusbiernew_LoRA"
--caption_column="prompt"
--mixed_precision="fp16"
--instance_prompt="a photo of [CB] beer"
--resolution=1024
--train_batch_size=1
--gradient_accumulation_steps=3
--gradient_checkpointing
--learning_rate=1e-4
--snr_gamma=5.0
--lr_scheduler="constant"
--lr_warmup_steps=0
--mixed_precision="fp16"
--use_8bit_adam
--max_train_steps=500
--checkpointing_steps=717
--seed="0"
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
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Base model
stabilityai/stable-diffusion-xl-base-1.0