Create app.py

app.py

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+import gradio as gr
+import torch
+from diffusers import DiffusionPipeline, DPMSolverMultistepScheduler
+from diffusers.utils import export_to_video
+import uuid
+
+# Model yükleme (Hafif ve hızlı versiyon)
+pipe = DiffusionPipeline.from_pretrained("ceruulean/zeroscope_v2_576w", torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32)
+pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
+
+# Eğer GPU varsa kullan, yoksa CPU (Free tier için otomatik ayar)
+if torch.cuda.is_available():
+    pipe.enable_model_cpu_offload()
+
+def generate_video(prompt):
+    video_frames = pipe(prompt, num_inference_steps=20, height=320, width=576, num_frames=24).frames
+    video_path = f"video_{uuid.uuid4()}.mp4"
+    export_to_video(video_frames[0], video_path)
+    return video_path
+
+# Gradio Arayüzü
+with gr.Blocks() as demo:
+    prompt = gr.Textbox(label="Video Promptu")
+    video_output = gr.Video(label="Üretilen Video")
+    generate_btn = gr.Button("Üret")
+    
+    generate_btn.click(fn=generate_video, inputs=prompt, outputs=video_output)
+
+demo.launch()