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num_frames = 16
frame_interval = 3
fps = 24
image_size = (240, 426)
multi_resolution = "STDiT2"
# Define model
model = dict(
type="STDiT2-XL/2",
from_pretrained="hpcai-tech/OpenSora-STDiT-v2-stage3",
input_sq_size=512,
qk_norm=True,
qk_norm_legacy=True,
enable_flash_attn=True,
enable_layernorm_kernel=True,
)
vae = dict(
type="VideoAutoencoderKL",
from_pretrained="stabilityai/sd-vae-ft-ema",
cache_dir=None, # "/mnt/hdd/cached_models",
micro_batch_size=4,
)
text_encoder = dict(
type="t5",
from_pretrained="DeepFloyd/t5-v1_1-xxl",
cache_dir=None, # "/mnt/hdd/cached_models",
model_max_length=200,
)
scheduler = dict(
type="iddpm",
num_sampling_steps=100,
cfg_scale=7.0,
cfg_channel=3, # or None
)
dtype = "bf16"
# Condition
prompt_path = "./assets/texts/t2v_samples.txt"
prompt = None # prompt has higher priority than prompt_path
# Others
batch_size = 1
seed = 42
save_dir = "./samples/samples/"
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