from fastvideo import VideoGenerator 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_pretrained( "Wan-AI/Wan2.2-T2V-A14B-Diffusers", # FastVideo will automatically handle distributed setup num_gpus=2, use_fsdp_inference=False, # set to True if GPU is out of memory dit_cpu_offload=True, # DiT need to be offloaded for MoE vae_cpu_offload=False, text_encoder_cpu_offload=True, # Set pin_cpu_memory to false if CPU RAM is limited and there're no frequent CPU-GPU transfer pin_cpu_memory=True, # image_encoder_cpu_offload=False, ) # 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({ "prompt": prompt, "sampling": { "height": 720, "width": 1280, "num_frames": 81, }, "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.") _ = generator.generate({ "prompt": prompt2, "sampling": { "height": 720, "width": 1280, "num_frames": 81, }, "output": { "output_path": OUTPUT_PATH, "save_video": True, }, }) if __name__ == "__main__": main()