xx

app.py

@@ -1,465 +1,470 @@
-#!/usr/bin/env python
-#patch 0.04
-#Func() Dalle Collage Moved Midjourney Space 
-#Pruned DalleCollage Space 
-import os
-import random
-import uuid
-import json
-
-import gradio as gr
-import numpy as np
-from PIL import Image
-import spaces
-import torch
-from diffusers import DiffusionPipeline
-from typing import Tuple
-
-#BaseConditions--
-bad_words = json.loads(os.getenv('BAD_WORDS', "[]"))
-bad_words_negative = json.loads(os.getenv('BAD_WORDS_NEGATIVE', "[]"))
-default_negative = os.getenv("default_negative","")
-
-def check_text(prompt, negative=""):
-    for i in bad_words:
-        if i in prompt:
-            return True
-    for i in bad_words_negative:
-        if i in negative:
-            return True
-    return False
-
-style_list = [
-    {
-        "name": "3840 x 2160",
-        "prompt": "hyper-realistic 8K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic",
-        "negative_prompt": "cartoonish, low resolution, blurry, simplistic, abstract, deformed, ugly",
-    },
-    {
-        "name": "2560 x 1440",
-        "prompt": "hyper-realistic 4K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic",
-        "negative_prompt": "cartoonish, low resolution, blurry, simplistic, abstract, deformed, ugly",
-    },
-
-    {
-        "name": "HD+",
-        "prompt": "hyper-realistic 2K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic",
-        "negative_prompt": "cartoonish, low resolution, blurry, simplistic, abstract, deformed, ugly",
-    },
-    
-    {
-        "name": "Style Zero",
-        "prompt": "{prompt}",
-        "negative_prompt": "",
-    },
-]
-
-collage_style_list = [
-    {
-        "name": "Hi-Res",
-        "prompt": "hyper-realistic 8K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic",
-        "negative_prompt": "cartoonish, low resolution, blurry, simplistic, abstract, deformed, ugly",
-    },
-    {
-        "name": "B & W",
-        "prompt": "black and white collage of {prompt}. monochromatic, timeless, classic, dramatic contrast",
-        "negative_prompt": "colorful, vibrant, bright, flashy",
-    },
-    {
-        "name": "Polaroid",
-        "prompt": "collage of polaroid photos featuring {prompt}. vintage style, high contrast, nostalgic, instant film aesthetic",
-        "negative_prompt": "digital, modern, low quality, blurry",
-    },
-    {
-        "name": "Watercolor",
-        "prompt": "watercolor collage of {prompt}. soft edges, translucent colors, painterly effects",
-        "negative_prompt": "digital, sharp lines, solid colors",
-    },
-    {
-        "name": "Cinematic",
-        "prompt": "cinematic collage of {prompt}. film stills, movie posters, dramatic lighting",
-        "negative_prompt": "static, lifeless, mundane",
-    },
-    {
-        "name": "Nostalgic",
-        "prompt": "nostalgic collage of {prompt}. retro imagery, vintage objects, sentimental journey",
-        "negative_prompt": "contemporary, futuristic, forward-looking",
-    },
-    {
-        "name": "Vintage",
-        "prompt": "vintage collage of {prompt}. aged paper, sepia tones, retro imagery, antique vibes",
-        "negative_prompt": "modern, contemporary, futuristic, high-tech",
-    },
-    {
-        "name": "Scrapbook",
-        "prompt": "scrapbook style collage of {prompt}. mixed media, hand-cut elements, textures, paper, stickers, doodles",
-        "negative_prompt": "clean, digital, modern, low quality",
-    },
-    {
-        "name": "NeoNGlow",
-        "prompt": "neon glow collage of {prompt}. vibrant colors, glowing effects, futuristic vibes",
-        "negative_prompt": "dull, muted colors, vintage, retro",
-    },
-    {
-        "name": "Geometric",
-        "prompt": "geometric collage of {prompt}. abstract shapes, colorful, sharp edges, modern design, high quality",
-        "negative_prompt": "blurry, low quality, traditional, dull",
-    },
-    {
-        "name": "Thematic",
-        "prompt": "thematic collage of {prompt}. cohesive theme, well-organized, matching colors, creative layout",
-        "negative_prompt": "random, messy, unorganized, clashing colors",
-    },
-
-    {
-        "name": "No Style",
-        "prompt": "{prompt}",
-        "negative_prompt": "",
-    },
-]
-
-filters = {
-    "Vivid": {
-        "prompt": "extra vivid {prompt}",
-        "negative_prompt": "washed out, dull"
-    },
-    "Playa": {
-        "prompt": "{prompt} set in a vast playa",
-        "negative_prompt": "forest, mountains"
-    },
-    "Desert": {
-        "prompt": "{prompt} set in a desert landscape",
-        "negative_prompt": "ocean, city"
-    },
-    "West": {
-        "prompt": "{prompt} with a western theme",
-        "negative_prompt": "eastern, modern"
-    },
-    "Blush": {
-        "prompt": "{prompt} with a soft blush color palette",
-        "negative_prompt": "harsh colors, neon"
-    },
-    "Minimalist": {
-        "prompt": "{prompt} with a minimalist design",
-        "negative_prompt": "cluttered, ornate"
-    },
-
-    "Zero filter": {
-        "prompt": "{prompt}",
-        "negative_prompt": ""
-    },
-    
-    
-}
-
-styles = {k["name"]: (k["prompt"], k["negative_prompt"]) for k in style_list}
-collage_styles = {k["name"]: (k["prompt"], k["negative_prompt"]) for k in collage_style_list}
-filter_styles = {k: (v["prompt"], v["negative_prompt"]) for k, v in filters.items()}
-STYLE_NAMES = list(styles.keys())
-COLLAGE_STYLE_NAMES = list(collage_styles.keys())
-FILTER_NAMES = list(filters.keys())
-DEFAULT_STYLE_NAME = "3840 x 2160"
-DEFAULT_COLLAGE_STYLE_NAME = "Hi-Res"
-DEFAULT_FILTER_NAME = "Vivid"
-
-def apply_style(style_name: str, positive: str, negative: str = "") -> Tuple[str, str]:
-    if style_name in styles:
-        p, n = styles.get(style_name, styles[DEFAULT_STYLE_NAME])
-    elif style_name in collage_styles:
-        p, n = collage_styles.get(style_name, collage_styles[DEFAULT_COLLAGE_STYLE_NAME])
-    elif style_name in filter_styles:
-        p, n = filter_styles.get(style_name, filter_styles[DEFAULT_FILTER_NAME])
-    else:
-        p, n = styles[DEFAULT_STYLE_NAME]
-    
-    if not negative:
-        negative = ""
-    return p.replace("{prompt}", positive), n + negative
-
-    
-
-DESCRIPTION = """## MidJourney
-
-Drop your best results in the community: [rb.gy/klkbs7](http://rb.gy/klkbs7), Have you tried the stable hamster space? [rb.gy/hfrm2f](http://rb.gy/hfrm2f)
-"""
-
-
-if not torch.cuda.is_available():
-    DESCRIPTION += "\n<p>⚠️Running on CPU, This may not work on CPU.</p>"
-
-MAX_SEED = np.iinfo(np.int32).max
-CACHE_EXAMPLES = torch.cuda.is_available() and os.getenv("CACHE_EXAMPLES", "0") == "1"
-MAX_IMAGE_SIZE = int(os.getenv("MAX_IMAGE_SIZE", "2048"))
-USE_TORCH_COMPILE = os.getenv("USE_TORCH_COMPILE", "0") == "1"
-ENABLE_CPU_OFFLOAD = os.getenv("ENABLE_CPU_OFFLOAD", "0") == "1"
-
-device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
-
-if torch.cuda.is_available():
-    pipe = DiffusionPipeline.from_pretrained(
-        "----you model goes here-----",
-        torch_dtype=torch.float16,
-        use_safetensors=True,
-        add_watermarker=False,
-        variant="fp16"
-    ).to(device)
-
-    if ENABLE_CPU_OFFLOAD:
-        pipe.enable_model_cpu_offload()
-    else:
-        pipe.to(device)
-        print("Loaded on Device!")
-
-    if USE_TORCH_COMPILE:
-        pipe.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True)
-        print("Model Compiled!")
-
-def save_image(img, path):
-    img.save(path)
-
-def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
-    if randomize_seed:
-        seed = random.randint(0, MAX_SEED)
-    return seed
-
-@spaces.GPU(enable_queue=True)
-def generate(
-    prompt: str,
-    negative_prompt: str = "",
-    use_negative_prompt: bool = False,
-    style: str = DEFAULT_STYLE_NAME,
-    collage_style: str = DEFAULT_COLLAGE_STYLE_NAME,
-    filter_name: str = DEFAULT_FILTER_NAME,
-    grid_size: str = "2x2",
-    seed: int = 0,
-    width: int = 1024,
-    height: int = 1024,
-    guidance_scale: float = 3,
-    randomize_seed: bool = False,
-    use_resolution_binning: bool = True,
-    progress=gr.Progress(track_tqdm=True),
-):
-    if check_text(prompt, negative_prompt):
-        raise ValueError("Prompt contains restricted words.")
-    
-    if collage_style != "No Style":
-        prompt, negative_prompt = apply_style(collage_style, prompt, negative_prompt)
-    elif filter_name != "No Filter":
-        prompt, negative_prompt = apply_style(filter_name, prompt, negative_prompt)
-    else:
-        prompt, negative_prompt = apply_style(style, prompt, negative_prompt)
-    
-    seed = int(randomize_seed_fn(seed, randomize_seed))
-    generator = torch.Generator().manual_seed(seed)
-
-    if not use_negative_prompt:
-        negative_prompt = ""  # type: ignore
-    negative_prompt += default_negative    
-
-    grid_sizes = {
-        "2x1": (2, 1),
-        "1x2": (1, 2),
-        "2x2": (2, 2),
-        "2x3": (2, 3),
-        "3x2": (3, 2),
-        "1x1": (1, 1)
-    }
-    
-    grid_size_x, grid_size_y = grid_sizes.get(grid_size, (2, 2))
-    num_images = grid_size_x * grid_size_y
-
-    options = {
-        "prompt": prompt,
-        "negative_prompt": negative_prompt,
-        "width": width,
-        "height": height,
-        "guidance_scale": guidance_scale,
-        "num_inference_steps": 20,
-        "generator": generator,
-        "num_images_per_prompt": num_images,
-        "use_resolution_binning": use_resolution_binning,
-        "output_type": "pil",
-    }
-    
-    torch.cuda.empty_cache()  # Clear GPU memory
-    images = pipe(**options).images
-
-    grid_img = Image.new('RGB', (width * grid_size_x, height * grid_size_y))
-
-    for i, img in enumerate(images[:num_images]):
-        grid_img.paste(img, (i % grid_size_x * width, i // grid_size_x * height))
-
-    unique_name = str(uuid.uuid4()) + ".png"
-    save_image(grid_img, unique_name)
-    return [unique_name], seed
-
-examples = [
-    "Portrait of a beautiful woman in a hat, summer outfit, with freckles on her face, in a close up shot, with sunlight, outdoors, in soft light, with a beach background, looking at the camera, with high resolution photography, in the style of Hasselblad X2D50c --ar 85:128 --v 6.0 --style raw",
-    "3d image, cute girl, in the style of Pixar --ar 1:2 --stylize 750, 4K resolution highlights, Sharp focus, octane render, ray tracing, Ultra-High-Definition, 8k, UHD, HDR, (Masterpiece:1.5), (best quality:1.5)",
-    "Cold coffee in a cup bokeh --ar 85:128 --v 6.0 --style raw5, 4K, Photo-Realistic",
-    "Closeup of blonde woman depth of field, bokeh, shallow focus, minimalism, fujifilm xh2s with Canon EF lens, cinematic --ar 85:128 --v 6.0 --style raw"
-]
-
-css = '''
-.gradio-container{max-width: 670px !important}
-h1{text-align:center}
-'''
-with gr.Blocks(css=css, theme="bethecloud/storj_theme") as demo:
-    gr.Markdown(DESCRIPTION)
-    gr.DuplicateButton(
-        value="Duplicate Space for private use",
-        elem_id="duplicate-button",
-        visible=os.getenv("SHOW_DUPLICATE_BUTTON") == "1",
-    )
-    with gr.Group():
-        with gr.Row():
-            prompt = gr.Text(
-                label="Prompt",
-                show_label=False,
-                max_lines=1,
-                placeholder="Enter your prompt",
-                container=False,
-            )
-            run_button = gr.Button("Run")
-        result = gr.Gallery(label="Grid", columns=1, preview=True)
-
-
-    with gr.Row(visible=True):
-        filter_selection = gr.Radio(
-            show_label=True,
-            container=True,
-            interactive=True,
-            choices=FILTER_NAMES,
-            value=DEFAULT_FILTER_NAME,
-            label="Filter Type",
-        )
-
-    with gr.Row(visible=True):
-        style_selection = gr.Radio(
-            show_label=True,
-            container=True,
-            interactive=True,
-            choices=STYLE_NAMES,
-            value=DEFAULT_STYLE_NAME,
-            label="Quality Style",
-        )
-
-    with gr.Row(visible=True):
-        collage_style_selection = gr.Radio(
-            show_label=True,
-            container=True,
-            interactive=True,
-            choices=COLLAGE_STYLE_NAMES,
-            value=DEFAULT_COLLAGE_STYLE_NAME,
-            label="Collage Template",
-        )
-    with gr.Row(visible=True):
-        grid_size_selection = gr.Dropdown(
-            choices=["2x1", "1x2", "2x2", "2x3", "3x2", "1x1"],
-            value="2x2",
-            label="Grid Size"
-        )
-
-    with gr.Accordion("Advanced options", open=False):
-        use_negative_prompt = gr.Checkbox(label="Use negative prompt", value=True, visible=True)
-        negative_prompt = gr.Text(
-            label="Negative prompt",
-            max_lines=1,
-            placeholder="Enter a negative prompt",
-            value="(deformed, distorted, disfigured:1.3), poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, (mutated hands and fingers:1.4), disconnected limbs, mutation, mutated, ugly, disgusting, blurry, amputation",
-            visible=True,
-        )
-        with gr.Row():
-            num_inference_steps = gr.Slider(
-                label="Steps",
-                minimum=10,
-                maximum=30,
-                step=1,
-                value=15,
-            )
-        with gr.Row():
-            num_images_per_prompt = gr.Slider(
-                label="Images",
-                minimum=1,
-                maximum=5,
-                step=1,
-                value=2,
-            )
-        seed = gr.Slider(
-            label="Seed",
-            minimum=0,
-            maximum=MAX_SEED,
-            step=1,
-            value=0,
-            visible=True
-        )
-        randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
-
-        with gr.Row(visible=True):
-            width = gr.Slider(
-                label="Width",
-                minimum=512,
-                maximum=2048,
-                step=8,
-                value=1024,
-            )
-            height = gr.Slider(
-                label="Height",
-                minimum=512,
-                maximum=2048,
-                step=8,
-                value=1024,
-            )
-
-        with gr.Row():
-            guidance_scale = gr.Slider(
-                label="Guidance Scale",
-                minimum=0.1,
-                maximum=20.0,
-                step=0.1,
-                value=6,
-            )
-
-    gr.Examples(
-        examples=examples,
-        inputs=prompt,
-        outputs=[result, seed],
-        fn=generate,
-        #cache_examples=True,
-        cache_examples=CACHE_EXAMPLES,
-    )
-
-    use_negative_prompt.change(
-        fn=lambda x: gr.update(visible=x),
-        inputs=use_negative_prompt,
-        outputs=negative_prompt,
-        api_name=False,
-    )
-
-    gr.on(
-        triggers=[
-            prompt.submit,
-            negative_prompt.submit,
-            run_button.click,
-        ],
-        fn=generate,
-        inputs=[
-            prompt,
-            negative_prompt,
-            use_negative_prompt,
-            style_selection,
-            collage_style_selection,
-            filter_selection,
-            grid_size_selection,
-            seed,
-            width,
-            height,
-            guidance_scale,
-            randomize_seed,
-        ],
-        outputs=[result, seed],
-        api_name="run",
-    )
-
-if __name__ == "__main__":
-    demo.queue(max_size=20).launch()
+#!/usr/bin/env python
+#patch 0.04
+#Func() Dalle Collage Moved Midjourney Space 
+#Pruned DalleCollage Space 
+import os
+import random
+import uuid
+import json
+
+import torch
+print(f"Is CUDA available: {torch.cuda.is_available()}")
+# True
+print(f"CUDA device: {torch.cuda.get_device_name(torch.cuda.current_device())}")
+# Tesla T4
+import gradio as gr
+import numpy as np
+from PIL import Image
+import spaces
+import torch
+from diffusers import DiffusionPipeline
+from typing import Tuple
+
+#BaseConditions--
+bad_words = json.loads(os.getenv('BAD_WORDS', "[]"))
+bad_words_negative = json.loads(os.getenv('BAD_WORDS_NEGATIVE', "[]"))
+default_negative = os.getenv("default_negative","")
+
+def check_text(prompt, negative=""):
+    for i in bad_words:
+        if i in prompt:
+            return True
+    for i in bad_words_negative:
+        if i in negative:
+            return True
+    return False
+
+style_list = [
+    {
+        "name": "3840 x 2160",
+        "prompt": "hyper-realistic 8K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic",
+        "negative_prompt": "cartoonish, low resolution, blurry, simplistic, abstract, deformed, ugly",
+    },
+    {
+        "name": "2560 x 1440",
+        "prompt": "hyper-realistic 4K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic",
+        "negative_prompt": "cartoonish, low resolution, blurry, simplistic, abstract, deformed, ugly",
+    },
+
+    {
+        "name": "HD+",
+        "prompt": "hyper-realistic 2K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic",
+        "negative_prompt": "cartoonish, low resolution, blurry, simplistic, abstract, deformed, ugly",
+    },
+    
+    {
+        "name": "Style Zero",
+        "prompt": "{prompt}",
+        "negative_prompt": "",
+    },
+]
+
+collage_style_list = [
+    {
+        "name": "Hi-Res",
+        "prompt": "hyper-realistic 8K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic",
+        "negative_prompt": "cartoonish, low resolution, blurry, simplistic, abstract, deformed, ugly",
+    },
+    {
+        "name": "B & W",
+        "prompt": "black and white collage of {prompt}. monochromatic, timeless, classic, dramatic contrast",
+        "negative_prompt": "colorful, vibrant, bright, flashy",
+    },
+    {
+        "name": "Polaroid",
+        "prompt": "collage of polaroid photos featuring {prompt}. vintage style, high contrast, nostalgic, instant film aesthetic",
+        "negative_prompt": "digital, modern, low quality, blurry",
+    },
+    {
+        "name": "Watercolor",
+        "prompt": "watercolor collage of {prompt}. soft edges, translucent colors, painterly effects",
+        "negative_prompt": "digital, sharp lines, solid colors",
+    },
+    {
+        "name": "Cinematic",
+        "prompt": "cinematic collage of {prompt}. film stills, movie posters, dramatic lighting",
+        "negative_prompt": "static, lifeless, mundane",
+    },
+    {
+        "name": "Nostalgic",
+        "prompt": "nostalgic collage of {prompt}. retro imagery, vintage objects, sentimental journey",
+        "negative_prompt": "contemporary, futuristic, forward-looking",
+    },
+    {
+        "name": "Vintage",
+        "prompt": "vintage collage of {prompt}. aged paper, sepia tones, retro imagery, antique vibes",
+        "negative_prompt": "modern, contemporary, futuristic, high-tech",
+    },
+    {
+        "name": "Scrapbook",
+        "prompt": "scrapbook style collage of {prompt}. mixed media, hand-cut elements, textures, paper, stickers, doodles",
+        "negative_prompt": "clean, digital, modern, low quality",
+    },
+    {
+        "name": "NeoNGlow",
+        "prompt": "neon glow collage of {prompt}. vibrant colors, glowing effects, futuristic vibes",
+        "negative_prompt": "dull, muted colors, vintage, retro",
+    },
+    {
+        "name": "Geometric",
+        "prompt": "geometric collage of {prompt}. abstract shapes, colorful, sharp edges, modern design, high quality",
+        "negative_prompt": "blurry, low quality, traditional, dull",
+    },
+    {
+        "name": "Thematic",
+        "prompt": "thematic collage of {prompt}. cohesive theme, well-organized, matching colors, creative layout",
+        "negative_prompt": "random, messy, unorganized, clashing colors",
+    },
+
+    {
+        "name": "No Style",
+        "prompt": "{prompt}",
+        "negative_prompt": "",
+    },
+]
+
+filters = {
+    "Vivid": {
+        "prompt": "extra vivid {prompt}",
+        "negative_prompt": "washed out, dull"
+    },
+    "Playa": {
+        "prompt": "{prompt} set in a vast playa",
+        "negative_prompt": "forest, mountains"
+    },
+    "Desert": {
+        "prompt": "{prompt} set in a desert landscape",
+        "negative_prompt": "ocean, city"
+    },
+    "West": {
+        "prompt": "{prompt} with a western theme",
+        "negative_prompt": "eastern, modern"
+    },
+    "Blush": {
+        "prompt": "{prompt} with a soft blush color palette",
+        "negative_prompt": "harsh colors, neon"
+    },
+    "Minimalist": {
+        "prompt": "{prompt} with a minimalist design",
+        "negative_prompt": "cluttered, ornate"
+    },
+
+    "Zero filter": {
+        "prompt": "{prompt}",
+        "negative_prompt": ""
+    },
+    
+    
+}
+
+styles = {k["name"]: (k["prompt"], k["negative_prompt"]) for k in style_list}
+collage_styles = {k["name"]: (k["prompt"], k["negative_prompt"]) for k in collage_style_list}
+filter_styles = {k: (v["prompt"], v["negative_prompt"]) for k, v in filters.items()}
+STYLE_NAMES = list(styles.keys())
+COLLAGE_STYLE_NAMES = list(collage_styles.keys())
+FILTER_NAMES = list(filters.keys())
+DEFAULT_STYLE_NAME = "3840 x 2160"
+DEFAULT_COLLAGE_STYLE_NAME = "Hi-Res"
+DEFAULT_FILTER_NAME = "Vivid"
+
+def apply_style(style_name: str, positive: str, negative: str = "") -> Tuple[str, str]:
+    if style_name in styles:
+        p, n = styles.get(style_name, styles[DEFAULT_STYLE_NAME])
+    elif style_name in collage_styles:
+        p, n = collage_styles.get(style_name, collage_styles[DEFAULT_COLLAGE_STYLE_NAME])
+    elif style_name in filter_styles:
+        p, n = filter_styles.get(style_name, filter_styles[DEFAULT_FILTER_NAME])
+    else:
+        p, n = styles[DEFAULT_STYLE_NAME]
+    
+    if not negative:
+        negative = ""
+    return p.replace("{prompt}", positive), n + negative
+
+    
+
+DESCRIPTION = """## MidJourney
+
+Drop your best results in the community: [rb.gy/klkbs7](http://rb.gy/klkbs7), Have you tried the stable hamster space? [rb.gy/hfrm2f](http://rb.gy/hfrm2f)
+"""
+
+
+if not torch.cuda.is_available():
+    DESCRIPTION += "\n<p>⚠️Running on CPU, This may not work on CPU.</p>"
+
+MAX_SEED = np.iinfo(np.int32).max
+CACHE_EXAMPLES = torch.cuda.is_available() and os.getenv("CACHE_EXAMPLES", "0") == "1"
+MAX_IMAGE_SIZE = int(os.getenv("MAX_IMAGE_SIZE", "2048"))
+USE_TORCH_COMPILE = os.getenv("USE_TORCH_COMPILE", "0") == "1"
+ENABLE_CPU_OFFLOAD = os.getenv("ENABLE_CPU_OFFLOAD", "0") == "1"
+
+device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
+
+if torch.cuda.is_available():
+    pipe = DiffusionPipeline.from_pretrained(
+        "----you model goes here-----",
+        torch_dtype=torch.float16,
+        use_safetensors=True,
+        add_watermarker=False,
+        variant="fp16"
+    ).to(device)
+
+    if ENABLE_CPU_OFFLOAD:
+        pipe.enable_model_cpu_offload()
+    else:
+        pipe.to(device)
+        print("Loaded on Device!")
+
+    if USE_TORCH_COMPILE:
+        pipe.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True)
+        print("Model Compiled!")
+
+def save_image(img, path):
+    img.save(path)
+
+def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
+    if randomize_seed:
+        seed = random.randint(0, MAX_SEED)
+    return seed
+
+@spaces.GPU(enable_queue=True)
+def generate(
+    prompt: str,
+    negative_prompt: str = "",
+    use_negative_prompt: bool = False,
+    style: str = DEFAULT_STYLE_NAME,
+    collage_style: str = DEFAULT_COLLAGE_STYLE_NAME,
+    filter_name: str = DEFAULT_FILTER_NAME,
+    grid_size: str = "2x2",
+    seed: int = 0,
+    width: int = 1024,
+    height: int = 1024,
+    guidance_scale: float = 3,
+    randomize_seed: bool = False,
+    use_resolution_binning: bool = True,
+    progress=gr.Progress(track_tqdm=True),
+):
+    if check_text(prompt, negative_prompt):
+        raise ValueError("Prompt contains restricted words.")
+    
+    if collage_style != "No Style":
+        prompt, negative_prompt = apply_style(collage_style, prompt, negative_prompt)
+    elif filter_name != "No Filter":
+        prompt, negative_prompt = apply_style(filter_name, prompt, negative_prompt)
+    else:
+        prompt, negative_prompt = apply_style(style, prompt, negative_prompt)
+    
+    seed = int(randomize_seed_fn(seed, randomize_seed))
+    generator = torch.Generator().manual_seed(seed)
+
+    if not use_negative_prompt:
+        negative_prompt = ""  # type: ignore
+    negative_prompt += default_negative    
+
+    grid_sizes = {
+        "2x1": (2, 1),
+        "1x2": (1, 2),
+        "2x2": (2, 2),
+        "2x3": (2, 3),
+        "3x2": (3, 2),
+        "1x1": (1, 1)
+    }
+    
+    grid_size_x, grid_size_y = grid_sizes.get(grid_size, (2, 2))
+    num_images = grid_size_x * grid_size_y
+
+    options = {
+        "prompt": prompt,
+        "negative_prompt": negative_prompt,
+        "width": width,
+        "height": height,
+        "guidance_scale": guidance_scale,
+        "num_inference_steps": 20,
+        "generator": generator,
+        "num_images_per_prompt": num_images,
+        "use_resolution_binning": use_resolution_binning,
+        "output_type": "pil",
+    }
+    
+    torch.cuda.empty_cache()  # Clear GPU memory
+    images = pipe(**options).images
+
+    grid_img = Image.new('RGB', (width * grid_size_x, height * grid_size_y))
+
+    for i, img in enumerate(images[:num_images]):
+        grid_img.paste(img, (i % grid_size_x * width, i // grid_size_x * height))
+
+    unique_name = str(uuid.uuid4()) + ".png"
+    save_image(grid_img, unique_name)
+    return [unique_name], seed
+
+examples = [
+    "Portrait of a beautiful woman in a hat, summer outfit, with freckles on her face, in a close up shot, with sunlight, outdoors, in soft light, with a beach background, looking at the camera, with high resolution photography, in the style of Hasselblad X2D50c --ar 85:128 --v 6.0 --style raw",
+    "3d image, cute girl, in the style of Pixar --ar 1:2 --stylize 750, 4K resolution highlights, Sharp focus, octane render, ray tracing, Ultra-High-Definition, 8k, UHD, HDR, (Masterpiece:1.5), (best quality:1.5)",
+    "Cold coffee in a cup bokeh --ar 85:128 --v 6.0 --style raw5, 4K, Photo-Realistic",
+    "Closeup of blonde woman depth of field, bokeh, shallow focus, minimalism, fujifilm xh2s with Canon EF lens, cinematic --ar 85:128 --v 6.0 --style raw"
+]
+
+css = '''
+.gradio-container{max-width: 670px !important}
+h1{text-align:center}
+'''
+with gr.Blocks(css=css, theme="bethecloud/storj_theme") as demo:
+    gr.Markdown(DESCRIPTION)
+    gr.DuplicateButton(
+        value="Duplicate Space for private use",
+        elem_id="duplicate-button",
+        visible=os.getenv("SHOW_DUPLICATE_BUTTON") == "1",
+    )
+    with gr.Group():
+        with gr.Row():
+            prompt = gr.Text(
+                label="Prompt",
+                show_label=False,
+                max_lines=1,
+                placeholder="Enter your prompt",
+                container=False,
+            )
+            run_button = gr.Button("Run")
+        result = gr.Gallery(label="Grid", columns=1, preview=True)
+
+
+    with gr.Row(visible=True):
+        filter_selection = gr.Radio(
+            show_label=True,
+            container=True,
+            interactive=True,
+            choices=FILTER_NAMES,
+            value=DEFAULT_FILTER_NAME,
+            label="Filter Type",
+        )
+
+    with gr.Row(visible=True):
+        style_selection = gr.Radio(
+            show_label=True,
+            container=True,
+            interactive=True,
+            choices=STYLE_NAMES,
+            value=DEFAULT_STYLE_NAME,
+            label="Quality Style",
+        )
+
+    with gr.Row(visible=True):
+        collage_style_selection = gr.Radio(
+            show_label=True,
+            container=True,
+            interactive=True,
+            choices=COLLAGE_STYLE_NAMES,
+            value=DEFAULT_COLLAGE_STYLE_NAME,
+            label="Collage Template",
+        )
+    with gr.Row(visible=True):
+        grid_size_selection = gr.Dropdown(
+            choices=["2x1", "1x2", "2x2", "2x3", "3x2", "1x1"],
+            value="2x2",
+            label="Grid Size"
+        )
+
+    with gr.Accordion("Advanced options", open=False):
+        use_negative_prompt = gr.Checkbox(label="Use negative prompt", value=True, visible=True)
+        negative_prompt = gr.Text(
+            label="Negative prompt",
+            max_lines=1,
+            placeholder="Enter a negative prompt",
+            value="(deformed, distorted, disfigured:1.3), poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, (mutated hands and fingers:1.4), disconnected limbs, mutation, mutated, ugly, disgusting, blurry, amputation",
+            visible=True,
+        )
+        with gr.Row():
+            num_inference_steps = gr.Slider(
+                label="Steps",
+                minimum=10,
+                maximum=30,
+                step=1,
+                value=15,
+            )
+        with gr.Row():
+            num_images_per_prompt = gr.Slider(
+                label="Images",
+                minimum=1,
+                maximum=5,
+                step=1,
+                value=2,
+            )
+        seed = gr.Slider(
+            label="Seed",
+            minimum=0,
+            maximum=MAX_SEED,
+            step=1,
+            value=0,
+            visible=True
+        )
+        randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
+
+        with gr.Row(visible=True):
+            width = gr.Slider(
+                label="Width",
+                minimum=512,
+                maximum=2048,
+                step=8,
+                value=1024,
+            )
+            height = gr.Slider(
+                label="Height",
+                minimum=512,
+                maximum=2048,
+                step=8,
+                value=1024,
+            )
+
+        with gr.Row():
+            guidance_scale = gr.Slider(
+                label="Guidance Scale",
+                minimum=0.1,
+                maximum=20.0,
+                step=0.1,
+                value=6,
+            )
+
+    gr.Examples(
+        examples=examples,
+        inputs=prompt,
+        outputs=[result, seed],
+        fn=generate,
+        #cache_examples=True,
+        cache_examples=CACHE_EXAMPLES,
+    )
+
+    use_negative_prompt.change(
+        fn=lambda x: gr.update(visible=x),
+        inputs=use_negative_prompt,
+        outputs=negative_prompt,
+        api_name=False,
+    )
+
+    gr.on(
+        triggers=[
+            prompt.submit,
+            negative_prompt.submit,
+            run_button.click,
+        ],
+        fn=generate,
+        inputs=[
+            prompt,
+            negative_prompt,
+            use_negative_prompt,
+            style_selection,
+            collage_style_selection,
+            filter_selection,
+            grid_size_selection,
+            seed,
+            width,
+            height,
+            guidance_scale,
+            randomize_seed,
+        ],
+        outputs=[result, seed],
+        api_name="run",
+    )
+
+if __name__ == "__main__":
+    demo.queue(max_size=20).launch()