Init commit

app.py

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+import gradio as gr
+import torch
+from torch import autocast
+from diffusers import StableDiffusionPipeline
+
+#model_id = "Deltaadams/Hentai-Diffusion"
+pipe = StableDiffusionPipeline.from_pretrained("Deltaadams/Hentai-Diffusion", torch_type=torch.float16, revision="fp16")
+pipe = pipe.to("cuda")
+#torch.backends.cudnn.benchmark = True
+num_samples = 2
+
+def infer(prompt):
+    images = pipe([prompt] * num_samples, guidance_scale=7.5)["sample"]
+    return images
+
+css = """
+        .gradio-container {
+            font-family: 'IBM Plex Sans', sans-serif;
+        }
+        .gr-button {
+            color: white;
+            border-color: black;
+            background: black;
+        }
+        input[type='range'] {
+            accent-color: black;
+        }
+        .dark input[type='range'] {
+            accent-color: #dfdfdf;
+        }
+        .container {
+            max-width: 730px;
+            margin: auto;
+            padding-top: 1.5rem;
+        }
+        #gallery {
+            min-height: 22rem;
+            margin-bottom: 15px;
+            margin-left: auto;
+            margin-right: auto;
+            border-bottom-right-radius: .5rem !important;
+            border-bottom-left-radius: .5rem !important;
+        }
+        #gallery>div>.h-full {
+            min-height: 20rem;
+        }
+        .details:hover {
+            text-decoration: underline;
+        }
+        .gr-button {
+            white-space: nowrap;
+        }
+        .gr-button:focus {
+            border-color: rgb(147 197 253 / var(--tw-border-opacity));
+            outline: none;
+            box-shadow: var(--tw-ring-offset-shadow), var(--tw-ring-shadow), var(--tw-shadow, 0 0 #0000);
+            --tw-border-opacity: 1;
+            --tw-ring-offset-shadow: var(--tw-ring-inset) 0 0 0 var(--tw-ring-offset-width) var(--tw-ring-offset-color);
+            --tw-ring-shadow: var(--tw-ring-inset) 0 0 0 calc(3px var(--tw-ring-offset-width)) var(--tw-ring-color);
+            --tw-ring-color: rgb(191 219 254 / var(--tw-ring-opacity));
+            --tw-ring-opacity: .5;
+        }
+        #advanced-btn {
+            font-size: .7rem !important;
+            line-height: 19px;
+            margin-top: 12px;
+            margin-bottom: 12px;
+            padding: 2px 8px;
+            border-radius: 14px !important;
+        }
+        #advanced-options {
+            display: none;
+            margin-bottom: 20px;
+        }
+        .footer {
+            margin-bottom: 45px;
+            margin-top: 35px;
+            text-align: center;
+            border-bottom: 1px solid #e5e5e5;
+        }
+        .footer>p {
+            font-size: .8rem;
+            display: inline-block;
+            padding: 0 10px;
+            transform: translateY(10px);
+            background: white;
+        }
+        .dark .footer {
+            border-color: #303030;
+        }
+        .dark .footer>p {
+            background: #0b0f19;
+        }
+        .acknowledgments h4{
+            margin: 1.25em 0 .25em 0;
+            font-weight: bold;
+            font-size: 115%;
+        }
+        #container-advanced-btns{
+            display: flex;
+            flex-wrap: wrap;
+            justify-content: space-between;
+            align-items: center;
+        }
+        .animate-spin {
+            animation: spin 1s linear infinite;
+        }
+        @keyframes spin {
+            from {
+                transform: rotate(0deg);
+            }
+            to {
+                transform: rotate(360deg);
+            }
+        }
+        #share-btn-container {
+            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;
+        }
+        #share-btn {
+            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;
+        }
+        #share-btn * {
+            all: unset;
+        }
+        .gr-form{
+            flex: 1 1 50%; border-top-right-radius: 0; border-bottom-right-radius: 0;
+        }
+        #prompt-container{
+            gap: 0;
+        }
+        #generated_id{
+            min-height: 700px
+        }
+"""
+block = gr.Blocks(css=css)
+
+examples = [
+#    [
+#        'TO'
+#    ],
+#    [
+#        'DO'
+#    ]
+]
+
+with block as demo:
+    gr.HTML(
+        """
+            <div style="text-align: center; max-width: 650px; margin: 0 auto;">
+              <div
+                style="
+                  display: inline-flex;
+                  align-items: center;
+                  gap: 0.8rem;
+                  font-size: 1.75rem;
+                "
+              >
+                <!--<img src="data:image/png;base64," />-->
+                <h1 style="font-weight: 900; margin-bottom: 7px;">
+                  Hentai Diffusion Demo
+                </h1>
+              </div>
+              <p style="margin-bottom: 10px; font-size: 94%">
+                text-to-image diffusion model based on HD model
+              </p>
+            </div>
+        """
+    )
+    with gr.Group():
+        with gr.Box():
+            with gr.Row().style(mobile_collapse=False, equal_height=True):
+
+                text = gr.Textbox(
+                    label="Enter your prompt", show_label=False, max_lines=1
+                ).style(
+                    border=(True, False, True, True),
+                    rounded=(True, False, False, True),
+                    container=False,
+                )
+                btn = gr.Button("Run").style(
+                    margin=False,
+                    rounded=(False, True, True, False),
+                )
+               
+        gallery = gr.Gallery(label="Generated images", show_label=False, elem_id="generated_id").style(
+            grid=[2], height="auto"
+        )
+        
+        ex = gr.Examples(examples=examples, fn=infer, inputs=[text], outputs=gallery, cache_examples=True)
+        ex.dataset.headers = [""]
+        
+        text.submit(infer, inputs=[text], outputs=gallery)
+        btn.click(infer, inputs=[text], outputs=gallery)
+
+    gr.HTML(
+            """
+                <div class="footer">
+                    <p>Stable Diffusion model by <a href="https://huggingface.co/Deltaadams" style="text-decoration: underline;" target="_blank">Deltaadams</a>
+                    </p>
+                </div>
+           """
+        )
+demo.queue(max_size=25).launch()

requirements.txt

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+--extra-index-url https://download.pytorch.org/whl/cu113
+torch
+diffusers==0.4.1
+huggingface-hub==0.10.0
+nvidia-ml-py3
+transformers==4.22.2
+ftfy
+scipy