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Mark000111888
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•
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Parent(s):
1241769
Update app.py
Browse files
app.py
CHANGED
@@ -1,269 +1,3 @@
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import gradio as gr
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import torch
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from huggingface_hub.repocard import RepoCard
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model_path = "Mark000111888/sd-model-finetuned-lora-t4"
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# model_path = "pcuenq/pokemon-lora"
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card = RepoCard.load(model_path)
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model_base = card.data.to_dict()["base_model"]
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print(model_base)
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pipe = StableDiffusionPipeline.from_pretrained(model_base, torch_dtype=torch.float16)
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pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
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pipe.unet.load_attn_procs(model_path)
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pipe.to("cuda")
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def infer(prompt, negative, scale):
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images = pipe(
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prompt, negative_prompt=negative, guidance_scale=scale,
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num_images_per_prompt=4, num_inference_steps=25
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).images
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return images
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css = """
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.gradio-container {
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font-family: 'IBM Plex Sans', sans-serif;
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}
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.gr-button {
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color: white;
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border-color: black;
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background: black;
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}
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input[type='range'] {
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accent-color: black;
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}
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.dark input[type='range'] {
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accent-color: #dfdfdf;
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}
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.container {
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max-width: 730px;
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margin: auto;
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padding-top: 1.5rem;
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}
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#gallery {
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min-height: 22rem;
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margin-bottom: 15px;
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margin-left: auto;
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margin-right: auto;
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border-bottom-right-radius: .5rem !important;
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border-bottom-left-radius: .5rem !important;
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}
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#gallery>div>.h-full {
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min-height: 20rem;
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}
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.details:hover {
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text-decoration: underline;
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}
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.gr-button {
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white-space: nowrap;
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}
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.gr-button:focus {
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border-color: rgb(147 197 253 / var(--tw-border-opacity));
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outline: none;
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box-shadow: var(--tw-ring-offset-shadow), var(--tw-ring-shadow), var(--tw-shadow, 0 0 #0000);
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--tw-border-opacity: 1;
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--tw-ring-offset-shadow: var(--tw-ring-inset) 0 0 0 var(--tw-ring-offset-width) var(--tw-ring-offset-color);
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--tw-ring-shadow: var(--tw-ring-inset) 0 0 0 calc(3px var(--tw-ring-offset-width)) var(--tw-ring-color);
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--tw-ring-color: rgb(191 219 254 / var(--tw-ring-opacity));
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--tw-ring-opacity: .5;
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}
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#advanced-btn {
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font-size: .7rem !important;
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line-height: 19px;
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margin-top: 12px;
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margin-bottom: 12px;
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padding: 2px 8px;
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border-radius: 14px !important;
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}
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#advanced-options {
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display: none;
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margin-bottom: 20px;
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}
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.footer {
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margin-bottom: 45px;
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margin-top: 35px;
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text-align: center;
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border-bottom: 1px solid #e5e5e5;
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}
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.footer>p {
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font-size: .8rem;
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display: inline-block;
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padding: 0 10px;
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transform: translateY(10px);
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background: white;
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}
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.dark .footer {
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border-color: #303030;
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}
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.dark .footer>p {
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background: #0b0f19;
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}
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.acknowledgments h4{
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margin: 1.25em 0 .25em 0;
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font-weight: bold;
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font-size: 115%;
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}
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.animate-spin {
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animation: spin 1s linear infinite;
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}
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@keyframes spin {
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from {
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transform: rotate(0deg);
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}
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to {
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transform: rotate(360deg);
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}
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}
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#share-btn-container {
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display: flex; padding-left: 0.5rem !important; padding-right: 0.5rem !important; background-color: #000000; justify-content: center; align-items: center; border-radius: 9999px !important; width: 13rem;
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margin-top: 10px;
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margin-left: auto;
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}
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#share-btn {
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all: initial; color: #ffffff;font-weight: 600; cursor:pointer; font-family: 'IBM Plex Sans', sans-serif; margin-left: 0.5rem !important; padding-top: 0.25rem !important; padding-bottom: 0.25rem !important;right:0;
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}
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#share-btn * {
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all: unset;
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}
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#share-btn-container div:nth-child(-n+2){
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width: auto !important;
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min-height: 0px !important;
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}
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#share-btn-container .wrap {
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display: none !important;
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}
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.gr-form{
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flex: 1 1 50%; border-top-right-radius: 0; border-bottom-right-radius: 0;
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}
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#prompt-container{
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gap: 0;
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}
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#prompt-text-input, #negative-prompt-text-input{padding: .45rem 0.625rem}
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#component-16{border-top-width: 1px!important;margin-top: 1em}
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.image_duplication{position: absolute; width: 100px; left: 50px}
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"""
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block = gr.Blocks(css=css)
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with block:
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gr.HTML(
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"""
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<div style="text-align: center; margin: 0 auto;">
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<div
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style="
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display: inline-flex;
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align-items: center;
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gap: 0.8rem;
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font-size: 1.75rem;
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"
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>
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<svg
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width="0.65em"
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height="0.65em"
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viewBox="0 0 115 115"
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fill="none"
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xmlns="http://www.w3.org/2000/svg"
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>
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<rect width="23" height="23" fill="white"></rect>
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<rect y="69" width="23" height="23" fill="white"></rect>
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<rect x="23" width="23" height="23" fill="#AEAEAE"></rect>
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<rect x="23" y="69" width="23" height="23" fill="#AEAEAE"></rect>
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<rect x="46" width="23" height="23" fill="white"></rect>
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<rect x="46" y="69" width="23" height="23" fill="white"></rect>
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<rect x="69" width="23" height="23" fill="black"></rect>
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<rect x="69" y="69" width="23" height="23" fill="black"></rect>
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<rect x="92" width="23" height="23" fill="#D9D9D9"></rect>
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<rect x="92" y="69" width="23" height="23" fill="#AEAEAE"></rect>
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<rect x="115" y="46" width="23" height="23" fill="white"></rect>
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<rect x="115" y="115" width="23" height="23" fill="white"></rect>
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<rect x="115" y="69" width="23" height="23" fill="#D9D9D9"></rect>
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<rect x="92" y="46" width="23" height="23" fill="#AEAEAE"></rect>
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<rect x="92" y="115" width="23" height="23" fill="#AEAEAE"></rect>
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<rect x="92" y="69" width="23" height="23" fill="white"></rect>
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<rect x="69" y="46" width="23" height="23" fill="white"></rect>
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<rect x="69" y="115" width="23" height="23" fill="white"></rect>
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<rect x="69" y="69" width="23" height="23" fill="#D9D9D9"></rect>
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<rect x="46" y="46" width="23" height="23" fill="black"></rect>
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<rect x="46" y="115" width="23" height="23" fill="black"></rect>
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<rect x="46" y="69" width="23" height="23" fill="black"></rect>
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<rect x="23" y="46" width="23" height="23" fill="#D9D9D9"></rect>
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<rect x="23" y="115" width="23" height="23" fill="#AEAEAE"></rect>
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<rect x="23" y="69" width="23" height="23" fill="black"></rect>
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</svg>
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<h1 style="font-weight: 900; margin-bottom: 7px;margin-top:5px">
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LoRA fine-tuning of Stable Diffusion
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</h1>
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</div>
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<p style="margin-bottom: 10px; font-size: 94%; line-height: 23px;">
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This demo showcases a Stable Diffusion model fine-tuned on <a href="https://huggingface.co/datasets/lambdalabs/pokemon-blip-captions" style="text-decoration: underline;" target="_blank">Lambda Labs Pokémon Dataset</a>, using a fast and efficient technique known as LoRA. The <a href="https://huggingface.co/sayakpaul/sd-model-finetuned-lora-t4" style="text-decoration: underline;" target="_blank">training result</a> is just a small (~3 MB) file that can be easily shared and downloaded. Feel free to check the source code to see how to use it!
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</p>
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</div>
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"""
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)
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with gr.Group():
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with gr.Box():
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with gr.Row(elem_id="prompt-container").style(mobile_collapse=False, equal_height=True):
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with gr.Column():
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text = gr.Textbox(
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label="Enter your prompt",
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show_label=False,
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max_lines=1,
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placeholder="Enter your prompt",
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elem_id="prompt-text-input",
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).style(
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border=(True, False, True, True),
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rounded=(True, False, False, True),
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container=False,
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)
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negative = gr.Textbox(
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label="Enter your negative prompt",
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show_label=False,
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max_lines=1,
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placeholder="Enter a negative prompt",
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elem_id="negative-prompt-text-input",
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).style(
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border=(True, False, True, True),
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rounded=(True, False, False, True),
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container=False,
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)
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btn = gr.Button("Generate image").style(
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margin=False,
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rounded=(False, True, True, False),
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full_width=False,
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)
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# output_image = gr.Image(label=f"Generated Image", show_label=False, type="pil", interactive=False)
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gallery = gr.Gallery(
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label="Generated images", show_label=False, type="pil", elem_id="gallery"
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).style(grid=[2], height="auto")
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with gr.Accordion("Advanced settings", open=False):
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guidance_scale = gr.Slider(
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label="Guidance Scale", minimum=0, maximum=50, value=9, step=0.1
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)
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negative.submit(infer, inputs=[text, negative, guidance_scale], outputs=[gallery])
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text.submit(infer, inputs=[text, negative, guidance_scale], outputs=[gallery])
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btn.click(infer, inputs=[text, negative, guidance_scale], outputs=[gallery])
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gr.HTML(
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"""
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<div class="footer">
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<p>Original model by <a href="https://huggingface.co/stabilityai" style="text-decoration: underline;" target="_blank">StabilityAI</a> – Fine-tuned by <a href="https://huggingface.co/sayakpaul/sd-model-finetuned-lora-t4" style="text-decoration: underline;" target="_blank">sayakpaul</a> on a T4 GPU – Gradio Demo by 🤗 <a href="https://huggingface.co/" style="text-decoration: underline;" target="_blank">Hugging Face</a>
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</p>
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</div>
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<div class="acknowledgments">
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<p><h4>LICENSE</h4>
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The model is licensed with a <a href="https://huggingface.co/stabilityai/stable-diffusion-2/blob/main/LICENSE-MODEL" style="text-decoration: underline;" target="_blank">CreativeML OpenRAIL++</a> license. The authors claim no rights on the outputs you generate, you are free to use them and are accountable for their use which must not go against the provisions set in this license. The license forbids you from sharing any content that violates any laws, produce any harm to a person, disseminate any personal information that would be meant for harm, spread misinformation and target vulnerable groups. For the full list of restrictions please <a href="https://huggingface.co/spaces/CompVis/stable-diffusion-license" target="_blank" style="text-decoration: underline;" target="_blank">read the license</a></p>
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<p><h4>Biases and content acknowledgment</h4>
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Despite how impressive being able to turn text into image is, beware to the fact that this model may output content that reinforces or exacerbates societal biases, as well as realistic faces, pornography and violence. The model was trained on the <a href="https://laion.ai/blog/laion-5b/" style="text-decoration: underline;" target="_blank">LAION-5B dataset</a>, which scraped non-curated image-text-pairs from the internet (the exception being the removal of illegal content) and is meant for research purposes. You can read more in the <a href="https://huggingface.co/CompVis/stable-diffusion-v1-4" style="text-decoration: underline;" target="_blank">model card</a></p>
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</div>
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"""
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)
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block.queue(concurrency_count=1).launch()
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import gradio as gr
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gr.Interface.load("models/Mark000111888/sd-model-finetuned-lora-t4").launch()
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