40 lines
1.8 KiB
Python
40 lines
1.8 KiB
Python
from fastvideo import VideoGenerator, PipelineConfig, SamplingParam
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# from fastvideo.configs.sample import SamplingParam
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OUTPUT_PATH = "video_samples_fp16"
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def main():
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# FastVideo will automatically use the optimal default arguments for the
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# model.
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# If a local path is provided, FastVideo will make a best effort
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# attempt to identify the optimal arguments.
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model = "Wan-AI/Wan2.1-T2V-1.3B-Diffusers"
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pipeline_config = PipelineConfig.from_pretrained(model)
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pipeline_config.text_encoder_precisions = ("bf16", )
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generator = VideoGenerator.from_pretrained(
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model,
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# if num_gpus > 1, FastVideo will automatically handle distributed setup
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pipeline_config=pipeline_config,
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use_fsdp_inference=False, # Disable FSDP for MPS
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dit_cpu_offload=True,
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text_encoder_cpu_offload=True,
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pin_cpu_memory=True,
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disable_autocast=False,
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num_gpus=1,
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)
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sampling_param = SamplingParam.from_pretrained(model)
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sampling_param.num_frames = 30
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# sampling_param.image_path = "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/astronaut.jpg"
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# Generate videos with the same simple API, regardless of GPU count
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prompt = "Will Smith casually eats noodles, his relaxed demeanor contrasting with the energetic background of a bustling street food market. The scene captures a mix of humor and authenticity. Mid-shot framing, vibrant lighting."
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video = generator.generate_video(prompt, output_path=OUTPUT_PATH, save_video=True, sampling_param=sampling_param)
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# video = generator.generate_video(prompt, sampling_param=sampling_param, output_path="wan_t2v_videos/")
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# Generate another video with a different prompt, without reloading the
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# model!
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if __name__ == "__main__":
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main()
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