CogVideoX-5B

Este modelo soporta despliegue usando la biblioteca huggingface diffusers. Puede desplegarlo siguiendo estos pasos. Se recomienda visitar nuestro GitHub y revisar las optimizaciones relevantes de prompt y conversiones para obtener una mejor experiencia.

Instalar las dependencias requeridas:

# diffusers>=0.30.1
# transformers>=4.44.2
# accelerate>=0.33.0 (sugerencia instalar desde el código fuente)
# imageio-ffmpeg>=0.5.1
pip install --upgrade transformers accelerate diffusers imageio-ffmpeg

Ejecutar el código:

import torch
from diffusers import CogVideoXPipeline
from diffusers.utils import export_to_video

prompt = "A panda, dressed in a small, red jacket and a tiny hat, sits on a wooden stool in a serene bamboo forest. The panda's fluffy paws strum a miniature acoustic guitar, producing soft, melodic tunes. Nearby, a few other pandas gather, watching curiously and some clapping in rhythm. Sunlight filters through the tall bamboo, casting a gentle glow on the scene. The panda's face is expressive, showing concentration and joy as it plays. The background includes a small, flowing stream and vibrant green foliage, enhancing the peaceful and magical atmosphere of this unique musical performance."

pipe = CogVideoXPipeline.from_pretrained(
"THUDM/CogVideoX-5b",
torch_dtype=torch.bfloat16
)

pipe.enable_model_cpu_offload()
pipe.vae.enable_tiling()

video = pipe(
prompt=prompt,
num_videos_per_prompt=1,
num_inference_steps=50,
num_frames=49,
guidance_scale=6,
generator=torch.Generator(device="cuda").manual_seed(42),
).frames[0]

export_to_video(video, "output.mp4", fps=8)