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import gradio as gr |
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from random import randint |
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from all_models import models |
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from externalmod import gr_Interface_load |
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import asyncio |
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import os |
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from threading import RLock |
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lock = RLock() |
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HF_TOKEN = os.environ.get("HF_TOKEN") if os.environ.get("HF_TOKEN") else None |
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def load_fn(models): |
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global models_load |
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models_load = {} |
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for model in models: |
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if model not in models_load.keys(): |
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try: |
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m = gr_Interface_load(f'models/{model}', hf_token=HF_TOKEN) |
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except Exception as error: |
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print(error) |
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m = gr.Interface(lambda: None, ['text'], ['image']) |
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models_load.update({model: m}) |
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load_fn(models) |
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num_models = 1 |
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default_models = models[:num_models] |
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inference_timeout = 600 |
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MAX_SEED=3999999999 |
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def extend_choices(choices): |
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return choices + (num_models - len(choices)) * ['NA'] |
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def update_imgbox(choices): |
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choices_plus = extend_choices(choices) |
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return [gr.Image(None, label = m, visible = (m != 'NA')) for m in choices_plus] |
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def gen_fn(model_str, prompt): |
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if model_str == 'NA': |
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return None |
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noise = str('') |
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return models_load[model_str](f'{prompt} {noise}') |
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async def infer(model_str, prompt, seed=1, timeout=inference_timeout): |
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from pathlib import Path |
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kwargs = {} |
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noise = "" |
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kwargs["seed"] = seed |
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task = asyncio.create_task(asyncio.to_thread(models_load[model_str].fn, |
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prompt=f'{prompt} {noise}', **kwargs, token=HF_TOKEN)) |
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await asyncio.sleep(0) |
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try: |
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result = await asyncio.wait_for(task, timeout=timeout) |
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except (Exception, asyncio.TimeoutError) as e: |
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print(e) |
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print(f"Task timed out: {model_str}") |
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if not task.done(): task.cancel() |
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result = None |
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if task.done() and result is not None: |
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with lock: |
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png_path = "image.png" |
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result.save(png_path) |
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image = str(Path(png_path).resolve()) |
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return image |
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return None |
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def gen_fnseed(model_str, prompt, seed=1): |
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if model_str == 'NA': |
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return None |
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try: |
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loop = asyncio.new_event_loop() |
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result = loop.run_until_complete(infer(model_str, prompt, seed, inference_timeout)) |
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except (Exception, asyncio.CancelledError) as e: |
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print(e) |
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print(f"Task aborted: {model_str}") |
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result = None |
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with lock: |
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image = "https://huggingface.co/spaces/Yntec/ToyWorld/resolve/main/error.png" |
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result = image |
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finally: |
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loop.close() |
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return result |
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def gen_fnsix(model_str, prompt): |
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if model_str == 'NA': |
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return None |
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noisesix = str(randint(1941, 2023)) |
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return models_load[model_str](f'{prompt} {noisesix}') |
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with gr.Blocks() as demo: |
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gr.HTML( |
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""" |
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<div> |
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<p> <center><img src="https://huggingface.co/Yntec/OpenGenDiffusers/resolve/main/pp.png" style="height:128px; width:482px; margin-top: -22px; margin-bottom: -44px;" span title="Free ai art image generator Printing Press"></center> |
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</p> |
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""" |
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) |
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gr.HTML( |
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""" |
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<div> |
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<p> <center>For negative prompts, Width and Height, and other features visit John6666's <a href="https://huggingface.co/spaces/John6666/PrintingPress4">Printing Press 4</a>!</center> |
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</p></div> |
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""" |
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) |
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with gr.Tab('One Image'): |
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model_choice = gr.Dropdown(models, label = f'Choose a model from the {len(models)} available! Try clearing the box and typing on it to filter them!', value = models[0], filterable = True) |
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txt_input = gr.Textbox(label = 'Your prompt:') |
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max_imagesone = 1 |
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num_imagesone = gr.Slider(1, max_imagesone, value = max_imagesone, step = 1, label = 'Nobody gets to see this label so I can put here whatever I want!', visible = False) |
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gen_button = gr.Button('Generate') |
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gen_button.click(lambda s: gr.update(interactive = True), None) |
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with gr.Row(): |
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output = [gr.Image(label = '') for _ in range(max_imagesone)] |
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for i, o in enumerate(output): |
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img_in = gr.Number(i, visible = False) |
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num_imagesone.change(lambda i, n: gr.update(visible = (i < n)), [img_in, num_imagesone], o, show_progress = False) |
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gen_event = gen_button.click(lambda i, n, m, t: gen_fn(m, t) if (i < n) else None, [img_in, num_imagesone, model_choice, txt_input], o, concurrency_limit=None, queue=False) |
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with gr.Row(): |
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gr.HTML( |
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""" |
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<div class="footer"> |
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<p> Based on the <a href="https://huggingface.co/spaces/derwahnsinn/TestGen">TestGen</a> Space by derwahnsinn, the <a href="https://huggingface.co/spaces/RdnUser77/SpacIO_v1">SpacIO</a> Space by RdnUser77, Omnibus's Maximum Multiplier, and <a href="https://huggingface.co/spaces/Yntec/ToyWorld">Toy World</a>! |
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</p> |
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""" |
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) |
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with gr.Tab('Seed it!'): |
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model_choiceseed = gr.Dropdown(models, label = f'Choose a model from the {len(models)} available! Try clearing the box and typing on it to filter them!', value = models[0], filterable = True) |
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txt_inputseed = gr.Textbox(label = 'Your prompt:') |
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seed = gr.Slider(label="Use a seed to replicate the same image later", info="Max 3999999999", minimum=0, maximum=MAX_SEED, step=1, value=1) |
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max_imagesseed = 1 |
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num_imagesseed = gr.Slider(1, max_imagesone, value = max_imagesone, step = 1, label = 'One, because more would make it produce identical images with the seed', visible = False) |
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gen_buttonseed = gr.Button('Generate an image using the seed') |
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gen_button.click(lambda s: gr.update(interactive = True), None) |
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with gr.Row(): |
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outputseed = [gr.Image(label = '') for _ in range(max_imagesseed)] |
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for i, o in enumerate(outputseed): |
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img_is = gr.Number(i, visible = False) |
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num_imagesseed.change(lambda i, n: gr.update(visible = (i < n)), [img_is, num_imagesseed], o, show_progress = False) |
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gen_eventseed = gr.on(triggers=[gen_buttonseed.click, txt_inputseed.submit], |
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fn=lambda i, n, m, t, n1: gen_fnseed(m, t, n1) if (i < n) else None, |
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inputs=[img_is, num_imagesseed, model_choiceseed, txt_inputseed, seed], outputs=[o], |
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concurrency_limit=None, queue=False) |
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with gr.Row(): |
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gr.HTML( |
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""" |
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<div class="footer"> |
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<p> Based on the <a href="https://huggingface.co/spaces/derwahnsinn/TestGen">TestGen</a> Space by derwahnsinn, the <a href="https://huggingface.co/spaces/RdnUser77/SpacIO_v1">SpacIO</a> Space by RdnUser77, Omnibus's Maximum Multiplier, and <a href="https://huggingface.co/spaces/Yntec/ToyWorld">Toy World</a>! |
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</p> |
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""" |
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) |
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with gr.Tab('Up To Six'): |
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model_choice2 = gr.Dropdown(models, label = f'Choose a model from the {len(models)} available! Try clearing the box and typing on it to filter them!', value = models[0], filterable = True) |
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txt_input2 = gr.Textbox(label = 'Your prompt:') |
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max_images = 6 |
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num_images = gr.Slider(1, max_images, value = max_images, step = 1, label = 'Number of images (if you want less than 6 decrease them slowly until they match the boxes below)') |
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gen_button2 = gr.Button('Generate up to 6 images in up to 3 minutes total') |
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gen_button2.click(lambda s: gr.update(interactive = True), None) |
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gr.HTML( |
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""" |
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<div style="text-align: center; max-width: 1200px; margin: 0 auto;"> |
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<div> |
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<body> |
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<div class="center"><p style="margin-bottom: 10px; color: #000000;">Scroll down to see more images (they generate in a random order).</p> |
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</div> |
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</body> |
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</div> |
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</div> |
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""" |
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) |
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with gr.Column(): |
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output2 = [gr.Image(label = '') for _ in range(max_images)] |
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for i, o in enumerate(output2): |
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img_i = gr.Number(i, visible = False) |
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num_images.change(lambda i, n: gr.update(visible = (i < n)), [img_i, num_images], o, show_progress = False) |
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gen_event2 = gen_button2.click(lambda i, n, m, t: gen_fnsix(m, t) if (i < n) else None, [img_i, num_images, model_choice2, txt_input2], o, concurrency_limit=None, queue=False) |
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with gr.Row(): |
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gr.HTML( |
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""" |
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<div class="footer"> |
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<p> Based on the <a href="https://huggingface.co/spaces/derwahnsinn/TestGen">TestGen</a> Space by derwahnsinn, the <a href="https://huggingface.co/spaces/RdnUser77/SpacIO_v1">SpacIO</a> Space by RdnUser77, Omnibus's Maximum Multiplier and <a href="https://huggingface.co/spaces/Yntec/ToyWorld">Toy World</a>! |
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</p> |
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""" |
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) |
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demo.queue(default_concurrency_limit=200, max_size=200) |
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demo.launch(show_api=False, max_threads=400) |