First commit

README.md

@@ -4,10 +4,11 @@ emoji: 🐨
 colorFrom: purple
 colorTo: red
 sdk: gradio
-sdk_version: 5.8.0
+sdk_version: 5.5.0
 app_file: app.py
-pinned: false
-short_description: AI Video Generator Mochi
+pinned: true
+license: apache-2.0
+short_description: Generate a video based on a text prompt using Mochi
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -0,0 +1,136 @@
+# Install required packages
+#!pip install accelerate torch gradio transformers git+https://github.com/huggingface/diffusers sentencepiece opencv-python
+
+import os
+
+# Define a fallback for environments without GPU
+if os.environ.get("SPACES_ZERO_GPU") is not None:
+    import spaces
+else:
+    class spaces:
+        @staticmethod
+        def GPU(func):
+            def wrapper(*args, **kwargs):
+                return func(*args, **kwargs)
+            return wrapper
+
+import torch
+from diffusers import DiffusionPipeline
+from diffusers.utils import export_to_video
+import gradio as gr
+
+# Application configuration
+TITLE = "AI Video Generator 🌟"
+DESCRIPTION = """\
+🌈 Transform your imagination into stunning videos using advanced AI technology with Mochi-1-preview.\
+Experience the magic of generative art! 🎥
+"""
+BUY_ME_A_COFFEE = """
+<a href="https://buymeacoffee.com/ruslanmv" target="_blank">
+    <button style="background-color: #FFDD00; border: none; color: black; 
+                    padding: 10px 20px; text-align: center; 
+                    text-decoration: none; display: inline-block; 
+                    font-size: 16px; margin: 4px 2px; cursor: pointer; 
+                    border-radius: 10px;">\
+        ☕ Buy Me a Coffee
+    </button>
+</a>
+"""
+MODEL_PRE_TRAINED_ID = "genmo/mochi-1-preview"
+EXAMPLES = [
+    [
+        "A colossal griffin perched atop a crumbling gothic castle, its golden wings outstretched against a blood-red sunset.  Below, a raging battle between knights and goblins unfolds amidst the ruins of a once-great city.  The air is filled with the clash of steel, the cries of the wounded, and the roar of the griffin's echoing cry.",
+        90,
+        30,
+    ],
+    [
+        "A serene mountaintop monastery above the clouds, with monks practicing \"\
+        Tai Chi at sunrise. The scene is filled with golden sunlight and \"\
+        swirling mist, as cherry blossoms fall gently in the breeze.",
+        70,
+        24,
+    ],
+    [
+        "An enchanted meadow where unicorns graze among glowing wildflowers. \"\
+        Wisps of light float in the air, and a sparkling waterfall cascades into \"\
+        a crystal-clear pond surrounded by colorful butterflies.",
+        60,
+        25,
+    ],
+    [
+        "A sprawling underwater utopia with bioluminescent architecture, giant \"\
+        jellyfish drifting gracefully, and schools of exotic fish weaving \"\
+        through coral tunnels. The city is alive with vibrant marine life.",
+        80,
+        30,
+    ],
+    [
+        "A vast alien desert with shimmering sands of gold and silver, \"\
+        punctuated by colossal crystal spires. Twin suns set in the distance, \"\
+        casting long, surreal shadows across the dunes.",
+        75,
+        28,
+    ],
+]
+
+# Load the pre-trained model
+pipe = DiffusionPipeline.from_pretrained(
+    MODEL_PRE_TRAINED_ID, variant="bf16", torch_dtype=torch.bfloat16
+)
+
+# Enable memory-saving optimizations
+pipe.enable_model_cpu_offload()
+pipe.enable_vae_tiling()
+
+@spaces.GPU(duration=240)
+def generate_video(prompt, num_frames=84, fps=30, high_quality=False):
+    """Generate a video based on the input prompt."""
+    if high_quality:
+        print("High quality option selected. Requires 42GB VRAM.")
+        if os.environ.get("SPACES_ZERO_GPU") is not None:
+            raise RuntimeError("High quality option may fail on ZeroGPU environments.")
+        with torch.autocast("cuda", torch.bfloat16, cache_enabled=False):
+            frames = pipe(prompt, num_frames=num_frames).frames[0]
+    else:
+        print("Standard quality option selected.")
+        frames = pipe(prompt, num_frames=num_frames).frames[0]
+
+    video_path = "generated_video.mp4"
+    export_to_video(frames, video_path, fps=fps)
+    return video_path
+
+# Define the Gradio interface
+interface = gr.Interface(
+    fn=generate_video,
+    inputs=[
+        gr.Textbox(lines=2, placeholder="Enter a vivid text prompt... 🔍"),
+        gr.Slider(minimum=1, maximum=240, value=84, label="Frames 🎥"),
+        gr.Slider(minimum=1, maximum=60, value=30, label="FPS (Frames Per Second) ⏱"),
+        gr.Checkbox(label="High Quality (Requires 42GB VRAM) 🛠"),
+    ],
+    outputs=gr.Video(label="Generated Video"),
+    title=TITLE,
+    description=DESCRIPTION,
+    examples=EXAMPLES,
+    article=BUY_ME_A_COFFEE,
+)
+
+# Apply custom CSS for better alignment
+interface.css = """
+.interface-title {
+    text-align: center;
+    font-size: 2em;
+    color: #4A90E2;
+    font-family: 'Arial', sans-serif;
+}
+.interface-description {
+    text-align: center;
+    font-size: 1.2em;
+    color: #333333;
+    margin-bottom: 20px;
+}
+"""
+
+# Launch the Gradio application
+if __name__ == "__main__":
+    interface.launch()

requirements.txt

@@ -0,0 +1,7 @@
+accelerate
+torch
+gradio
+transformers
+git+https://github.com/huggingface/diffusers
+sentencepiece
+opencv-python