import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("Erland/tiny-fastwan2.1-t2v-dmd-debug", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]Tiny FastWan2.1 T2V DMD Debug Pipeline
This is a randomly initialized, tiny WanDMDPipeline fixture for FastVideo/FastWan2.1-T2V-1.3B-Diffusers.
FastVideo FastWan2.1 DMD-style text-to-video layout represented as a Diffusers-format artifact with _class_name patched to WanDMDPipeline for FastVideo VideoGenerator load-path debugging.
It is intended for fast load-path and inference-control debugging only. It is not trained and should not be used for generation quality evaluation.
import os
from fastvideo import VideoGenerator
os.environ["FASTVIDEO_ATTENTION_BACKEND"] = "TORCH_SDPA"
generator = VideoGenerator.from_pretrained(
"Erland/tiny-fastwan2.1-t2v-dmd-debug",
num_gpus=1,
)
try:
generator.generate_video(
"debug prompt",
output_path="my_videos/",
save_video=True,
)
finally:
generator.shutdown()
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