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import torch
import gradio as gr
from diffusers import DiffusionPipeline, DPMSolverMultistepScheduler
from diffusers.utils import export_to_video
# Отключение CUDA (GPU)
torch.device('cuda')
def generate_video(prompt):
# load pipeline
pipe = DiffusionPipeline.from_pretrained("damo-vilab/text-to-video-ms-1.7b", torch_dtype=torch.float16, variant="fp16").device
pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config).device
# optimize for GPU memory
pipe.enable_model_cpu_offload()
pipe.enable_vae_slicing()
# generate
video_frames = pipe(prompt, num_inference_steps=25, num_frames=200).frames
# convert to video
video_path = export_to_video(video_frames)
return video_path
demo = gr.Interface(fn=generate_video, inputs="text", outputs="file")
demo.launch(share=True) |