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import torch
from diffusers import StableDiffusionPipeline
import gradio as gr
model_base = "runwayml/stable-diffusion-v1-5"
lora_model_path = "Krebzonide/3a0s-w68r-4qw1-0"
pipe = StableDiffusionPipeline.from_pretrained(model_base, torch_dtype=torch.float16, use_safetensors=True)
pipe.unet.load_attn_procs(lora_model_path) #working, commented to text base model------------------------------------
#pipe.unet.load_attn_procs(lora_model_path, use_auth_token=True) test accessing a private model----------------------
pipe.to("cuda")
css = """
.btn-green {
background-image: linear-gradient(to bottom right, #86efac, #22c55e) !important;
border-color: #22c55e !important;
color: #166534 !important;
}
.btn-green:hover {
background-image: linear-gradient(to bottom right, #86efac, #86efac) !important;
}
.btn-red {
background: linear-gradient(to bottom right, #fda4af, #fb7185) !important;
border-color: #fb7185 !important;
color: #9f1239 !important;
}
.btn-red:hover {background: linear-gradient(to bottom right, #fda4af, #fda4af) !important;}
/*****/
.dark .btn-green {
background-image: linear-gradient(to bottom right, #047857, #065f46) !important;
border-color: #047857 !important;
color: #ffffff !important;
}
.dark .btn-green:hover {
background-image: linear-gradient(to bottom right, #047857, #047857) !important;
}
.dark .btn-red {
background: linear-gradient(to bottom right, #be123c, #9f1239) !important;
border-color: #be123c !important;
color: #ffffff !important;
}
.dark .btn-red:hover {background: linear-gradient(to bottom right, #be123c, #be123c) !important;}
"""
def generate(prompt, neg_prompt):
images = pipe(prompt,negative_prompt=neg_prompt,num_inference_steps=25,guidance_scale=6, cross_attention_kwargs={"scale": 0.5}).images
return [(img, f"Image {i+1}") for i, img in enumerate(images)]
with gr.Blocks(css=css) as demo:
with gr.Column():
prompt = gr.Textbox(label="Prompt")
negative_prompt = gr.Textbox(label="Negative Prompt", value="lowres, bad anatomy, bad hands, cropped, worst quality, disfigured, deformed, extra limbs, asian, filter, render")
submit_btn = gr.Button("Generate", variant="primary", min_width="96px")
gallery = gr.Gallery(label="Generated images")
submit_btn.click(generate, [prompt, negative_prompt], [gallery], queue=True)
demo.queue(1)
demo.launch(debug=True) |