[Feat] Support Self-Forcing's Causal Inference for Wan2.1 T2V 1.3B (#766)

Co-authored-by: SolitaryThinker <wlsaidhi@gmail.com>
This commit is contained in:
Wei Zhou
2025-08-28 16:47:49 -07:00
committed by GitHub
co-authored by SolitaryThinker
parent 7c554e5da8
commit ce67cd3729
19 changed files with 1412 additions and 30 deletions
@@ -0,0 +1,31 @@
import os
import time
from fastvideo import VideoGenerator, SamplingParam
OUTPUT_PATH = "video_samples_causal"
def main():
# FastVideo will automatically use the optimal default arguments for the
# model.
# If a local path is provided, FastVideo will make a best effort
# attempt to identify the optimal arguments.
model_name = "wlsaidhi/SFWan2.1-T2V-1.3B-Diffusers"
generator = VideoGenerator.from_pretrained(
model_name,
# FastVideo will automatically handle distributed setup
num_gpus=1,
use_fsdp_inference=True,
text_encoder_cpu_offload=False,
dit_cpu_offload=False,
)
sampling_param = SamplingParam.from_pretrained(model_name)
prompt = (
"A curious raccoon peers through a vibrant field of yellow sunflowers, its eyes "
"wide with interest. The playful yet serene atmosphere is complemented by soft "
"natural light filtering through the petals. Mid-shot, warm and cheerful tones."
)
video = generator.generate_video(prompt, output_path=OUTPUT_PATH, save_video=True, sampling_param=sampling_param)
if __name__ == "__main__":
main()