These are stablediffusionapi/my-stablediffusion-lora-2855 LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0. The weights were trained using Modelslab. LoRA for the text encoder was enabled: False. Special VAE used for training: None.

Use it with the 🧨 diffusers library

!pip install -q transformers accelerate peft diffusers
from diffusers import DiffusionPipeline
import torch

pipe_id = "stabilityai/stable-diffusion-xl-base-1.0"
pipe = DiffusionPipeline.from_pretrained(pipe_id, torch_dtype=torch.float16).to("cuda")
pipe.load_lora_weights("stablediffusionapi/my-stablediffusion-lora-2855", weight_name="pytorch_lora_weights.safetensors", adapter_name="abc")
prompt = "abc of a hacker with a hoodie"
lora_scale = 0.9
image = pipe(
    prompt,
    num_inference_steps=30,
    cross_attention_kwargs={"scale": lora_scale},
    generator=torch.manual_seed(0)
).images[0]
image

Trigger words

You should use De Bruyne to trigger the image generation.

Download model

Weights for this model are available in Safetensors format. Download them in the Files & versions tab.