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+import gradio as gr
+from PIL import Image  
+import torch
+from muse import PipelineMuse
+from diffusers import AutoPipelineForText2Image, UniPCMultistepScheduler
+
+muse_512 = PipelineMuse.from_pretrained("openMUSE/muse-512").to("cuda", dtype=torch.float16)
+muse_512.transformer.enable_xformers_memory_efficient_attention()
+
+muse_512_fine = PipelineMuse.from_pretrained("openMUSE/muse-512-finetuned").to("cuda", dtype=torch.float16)
+muse_512_fine.transformer.enable_xformers_memory_efficient_attention()
+
+
+sdv1_5 = AutoPipelineForText2Image.from_pretrained("runwayml/stable-diffusion-v1-5", variant="fp16").to("cuda", dtype=torch.float16)
+sdv1_5.scheduler = UniPCMultistepScheduler.from_config(sdv1_5.scheduler.config)
+sdv1_5.enable_xformers_memory_efficient_attention()
+
+def infer(prompt, negative):
+    print("Generating:")
+
+    muse_512_image = muse_512(
+        prompt, timesteps=16, guidance_scale=10, transformer_seq_len=1024, use_fp16=True, temperature=(2, 0), 
+    )[0]
+
+    muse_512_fine_image = muse_512_fine(
+        prompt, timesteps=16, guidance_scale=10, transformer_seq_len=1024, use_fp16=True, temperature=(2, 0), 
+    )[0]
+
+    sdv1_5_image = sdv1_5(prompt, num_inference_steps=25).images[0]
+
+    images = [muse_512_image, muse_512_fine_image, sdv1_5_image]
+
+    return images
+
+
+examples = [
+    [
+        'A high tech solarpunk utopia in the Amazon rainforest',
+        'low quality',
+        10,
+    ],
+    [
+        'A pikachu fine dining with a view to the Eiffel Tower',
+        'low quality',
+        10,
+    ],
+    [
+        'A mecha robot in a favela in expressionist style',
+        'low quality, 3d, photorealistic',
+        10,
+    ],
+    [
+        'an insect robot preparing a delicious meal',
+        'low quality, illustration',
+        10,
+    ],
+    [
+        "A small cabin on top of a snowy mountain in the style of Disney, artstation",
+        'low quality, ugly',
+        10,
+    ],
+]
+    
+    
+css = """
+h1 {
+  text-align: center;
+}
+
+#component-0 {
+  max-width: 730px;
+  margin: auto;
+}
+"""
+
+block = gr.Blocks(css=css)
+
+with block:
+    gr.Markdown("MUSE is an upcoming fast text2image model.")
+    with gr.Group():
+        with gr.Row(elem_id="prompt-container").style(mobile_collapse=False, equal_height=True):
+            with gr.Column():
+                text = gr.Textbox(
+                    label="Enter your prompt",
+                    show_label=False,
+                    max_lines=1,
+                    placeholder="Enter your prompt",
+                    container=False,
+                )
+            btn = gr.Button("Generate image", scale=0)
+
+        gallery = gr.Gallery(
+            label="Generated images", show_label=False,
+        ).style()
+
+    with gr.Accordion("Advanced settings", open=False):
+        guidance_scale = gr.Slider(
+            label="Guidance Scale", minimum=0, maximum=20, value=10, step=0.1
+        )
+
+    ex = gr.Examples(examples=examples, fn=infer, inputs=[text, negative, guidance_scale], outputs=gallery, cache_examples=False)
+    ex.dataset.headers = [""]
+
+    text.submit(infer, inputs=[text, negative, guidance_scale], outputs=gallery)
+    negative.submit(infer, inputs=[text, negative, guidance_scale], outputs=gallery)
+    btn.click(infer, inputs=[text, negative, guidance_scale], outputs=gallery)
+
+block.launch()