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hao-ai-lab-FastVideo/t2v_debug_multi.sh
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# export WANDB_MODE="offline"
accelerate launch \
--config_file scripts/accelerate_configs/deepspeed_zero2_config.yaml \
opensora/train/train_t2v_diffusers.py \
--model OpenSoraT2V-ROPE-L/122 \
--pretrained data/Open-Sora-Plan-v1.2.0/29x480p/diffusion_pytorch_model.safetensors \
--text_encoder_name google/mt5-xxl \
--cache_dir "data/.cache" \
--dataset t2v \
--data "data/dummyVid/merge.txt" \
--ae CausalVAEModel_D4_4x8x8 \
--ae_path "data/Open-Sora-Plan-v1.2.0/vae" \
--sample_rate 1 \
--num_frames 29 \
--train_fps 24 \
--video_length_tolerance_range 200 \
--max_height 480 \
--max_width 640 \
--interpolation_scale_t 1.0 \
--interpolation_scale_h 1.0 \
--interpolation_scale_w 1.0 \
--attention_mode xformers \
--gradient_checkpointing \
--train_batch_size=1 \
--dataloader_num_workers 1 \
--gradient_accumulation_steps=1 \
--max_train_steps=1000000 \
--learning_rate=1e-4 \
--lr_scheduler="constant" \
--lr_warmup_steps=0 \
--mixed_precision="bf16" \
--report_to="wandb" \
--checkpointing_steps=250 \
--allow_tf32 \
--model_max_length 512 \
--use_image_num 0 \
--tile_overlap_factor 0.125 \
--snr_gamma 5.0 \
--use_ema \
--ema_start_step 0 \
--cfg 0.1 \
--noise_offset 0.02 \
--use_rope \
--resume_from_checkpoint="latest" \
--ema_decay 0.999 \
--enable_tiling \
--speed_factor 1.0 \
--group_frame \
--sp_size 2 \
--train_sp_batch_size 1 \
--output_dir="outputs/debug" \