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hao-ai-lab-FastVideo/examples/inference/basic/basic_turbodiffusion.py
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Davids048andClaude Opus 5.5 f571621ae7 [refactor]: move examples to generate(request) and from_config
Every example calls VideoGenerator.generate with a nested request instead
of generate_video keywords, and passes settings outside the from_pretrained
convenience keywords through VideoGenerator.from_config at their typed
paths. Each request and generator config equals what the keyword call built.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_012M91wnVFmPEvJ9h39r5BH7
2026-10-03 02:14:36 +00:00

60 lines
2.1 KiB
Python

import os
# Set SLA attention backend BEFORE fastvideo imports
os.environ["FASTVIDEO_ATTENTION_BACKEND"] = "SLA_ATTN"
from fastvideo import VideoGenerator
OUTPUT_PATH = "video_samples_turbodiffusion"
def main() -> None:
# TurboDiffusion: 1-4 step video generation using RCM scheduler + SLA attention
# FastVideo will automatically use TurboDiffusionPipeline when specified
generator = VideoGenerator.from_pretrained(
"loayrashid/TurboWan2.1-T2V-1.3B-Diffusers",
# FastVideo will automatically handle distributed setup
num_gpus=1,
use_fsdp_inference=False, # set to True if GPU is out of memory
# set to false if using RTX 4090
# pin_cpu_memory=False,
)
# Generate videos with the same simple API, regardless of GPU count
# TurboDiffusion defaults: guidance_scale=1.0 and num_inference_steps=4 (from 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.")
video = generator.generate({
"prompt": prompt,
"sampling": {
"seed": 42,
},
"output": {
"output_path": OUTPUT_PATH,
"save_video": True,
},
})
# Generate another video with a different prompt, without reloading the model!
prompt2 = ("A majestic lion strides across the golden savanna, its powerful frame "
"glistening under the warm afternoon sun. The tall grass ripples gently in "
"the breeze, enhancing the lion's commanding presence. The tone is vibrant, "
"embodying the raw energy of the wild. Low angle, steady tracking shot, "
"cinematic.")
video2 = generator.generate({
"prompt": prompt2,
"sampling": {
"seed": 42,
},
"output": {
"output_path": OUTPUT_PATH,
"save_video": True,
},
})
if __name__ == "__main__":
main()