from fastvideo import VideoGenerator from fastvideo.api import ( EngineConfig, GenerationRequest, GeneratorConfig, OffloadConfig, OutputConfig, SamplingConfig, ) OUTPUT_PATH = "video_samples_wan2_2_14B_t2v" 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. generator = VideoGenerator.from_config( GeneratorConfig( model_path="Wan-AI/Wan2.2-T2V-A14B-Diffusers", engine=EngineConfig( # FastVideo will automatically handle distributed setup num_gpus=2, use_fsdp_inference=False, # set to True if GPU is out of memory offload=OffloadConfig( dit=True, # DiT need to be offloaded for MoE vae=False, text_encoder=True, # Set pin_cpu_memory to false if CPU RAM is limited and there're no frequent CPU-GPU transfer pin_cpu_memory=True, ), ), ) ) # Generate videos with the same simple API, regardless of GPU count 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." ) _ = generator.generate( GenerationRequest( prompt=prompt, sampling=SamplingConfig(height=720, width=1280, num_frames=81), output=OutputConfig(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.") _ = generator.generate( GenerationRequest( prompt=prompt2, sampling=SamplingConfig(height=720, width=1280, num_frames=81), output=OutputConfig(output_path=OUTPUT_PATH, save_video=True), ) ) if __name__ == "__main__": main()