Files
hao-ai-lab-FastVideo/examples/inference/optimizations/text_encoder_quant_example.py
T

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2.2 KiB
Python

from fastvideo import VideoGenerator
import argparse
OUTPUT_PATH = "video_samples_wan2_2_5B_ti2v"
def main(text_encoder_path: str):
# 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 = "Wan-AI/Wan2.2-TI2V-5B-Diffusers"
generator = VideoGenerator.from_pretrained(
model_name,
# FastVideo will automatically handle distributed setup
num_gpus=1,
use_fsdp_inference=True,
dit_cpu_offload=True,
vae_cpu_offload=False,
text_encoder_cpu_offload=False,
# AbsMaxFP8 is the quantization method used by ComfyUI;
# check fastvideo/layers/quantization/* for more quantization methods
override_text_encoder_quant="AbsMaxFP8",
# for Wan 2.2, this is the path to "umt5_xxl_fp8_e4m3fn_scaled.safetensors"
override_text_encoder_safetensors=text_encoder_path,
pin_cpu_memory=True, # set to false if low CPU RAM or hit obscure "CUDA error: Invalid argument"
)
# I2V is triggered just by passing in an image_path argument
prompt = "Summer beach vacation style, a white cat wearing sunglasses sits on a surfboard. The fluffy-furred feline gazes directly at the camera with a relaxed expression. Blurred beach scenery forms the background featuring crystal-clear waters, distant green hills, and a blue sky dotted with white clouds. The cat assumes a naturally relaxed posture, as if savoring the sea breeze and warm sunlight. A close-up shot highlights the feline's intricate details and the refreshing atmosphere of the seaside."
image_path = "https://huggingface.co/datasets/YiYiXu/testing-images/resolve/main/wan_i2v_input.JPG"
video = generator.generate_video(
prompt, output_path=OUTPUT_PATH, save_video=True, image_path=image_path
)
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument(
"--text_encoder_path",
type=str,
required=True,
help="Path to the quantized text encoder safetensors file.",
)
args = parser.parse_args()
main(args.text_encoder_path)