| import gradio as gr |
| from diffusers import CogVideoXPipeline |
| import torch |
|
|
| model_name = "THUDM/CogVideoX-5b" |
| device = "cuda" if torch.cuda.is_available() else "cpu" |
|
|
| if device == "cuda": |
| pipe = CogVideoXPipeline.from_pretrained(model_name,torch_dtype=torch.float16).to(device) |
| else: |
| pipe = CogVideoXPipeline.from_pretrained(model_name).to(device) |
|
|
| def generate_video(prompt): |
| video = pipe(prompt, num_inference_steps=50, guidance_scale=9.5).videos |
|
|
| video_path = "generated_video.mp4" |
|
|
| video[0].save(video_path) |
|
|
| return video_path |
|
|
| iface = gr.Interface( |
| fn=generate_video, |
| inputs="text", |
| outputs="video", |
| title="BL's T2V Generator" |
| ) |
|
|
| iface.launch() |
|
|
