Files
hao-ai-lab-FastVideo/examples/inference/basic/basic_self_forcing_causal.py
T
SolitaryThinker bbbb7ab021 [refactor]: migrate examples/scripts to typed VideoGenerator API; rename api/compat.py to api/translation.py
Move all examples/inference and scripts off the legacy
VideoGenerator.from_pretrained(model, **kwargs) +
generate_video(prompt, **kwargs) surface onto the typed
from_config(GeneratorConfig(...)) + generate(GenerationRequest(...))
convention, including the Kandinsky-5 and DreamX-World examples added
on main after the original migration. git-mv api/compat.py to
api/translation.py ('compat' implied a temporary shim; the forward
translation is its honest permanent role) and repoint all importers,
tests, and doc links.
2026-07-11 03:26:24 -07:00

50 lines
1.5 KiB
Python

import os
import time
from fastvideo import VideoGenerator
from fastvideo.api import (
EngineConfig,
GenerationRequest,
GeneratorConfig,
OffloadConfig,
OutputConfig,
)
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_config = GeneratorConfig(
model_path=model_name,
# FastVideo will automatically handle distributed setup
engine=EngineConfig(
num_gpus=1,
use_fsdp_inference=False, # set to True if GPU is out of memory
offload=OffloadConfig(
text_encoder=False,
dit=False,
),
),
)
generator = VideoGenerator.from_config(generator_config)
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."
)
request = GenerationRequest(
prompt=prompt,
output=OutputConfig(
output_path=OUTPUT_PATH,
save_video=True,
),
)
video = generator.generate(request)
if __name__ == "__main__":
main()