Text-to-Image
Diffusers
Trained with AutoTrain
stable-diffusion
stable-diffusion-diffusers
lora
template:sd-lora
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("Lykon/DreamShaper", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("stablediffusionapi/my-stablediffusion-lora-2548")
prompt = "best quality, aqua eyes, baseball cap, closed mouth, green background, hat, looking at viewer, shirt, short hair, simple background, solo, upper body, yellow shirt"
image = pipe(prompt).images[0]AutoTrain LoRA DreamBooth - stablediffusionapi/my-stablediffusion-lora-2548
These are LoRA adaption weights for Lykon/DreamShaper. The weights were trained on best quality, aqua eyes, baseball cap, closed mouth, green background, hat, looking at viewer, shirt, short hair, simple background, solo, upper body, yellow shirt using DreamBooth. LoRA for the text encoder was enabled: False.
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Model tree for stablediffusionapi/my-stablediffusion-lora-2548
Base model
Lykon/DreamShaper