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sudo apt-get update && sudo apt-get install cbm git-lfs ffmpeg1git clone https://huggingface.co/svjack/Chinese_Children_wan_2_1_1_3_B_text2video_lora
2cd Chinese_Children_wan_2_1_1_3_B_text2video_lora 1pip install torch torchvision
2pip install -r requirements.txt
3pip install ascii-magic matplotlib tensorboard huggingface_hub datasets
4pip install moviepy==1.0.3
5pip install sageattention==1.0.61wget https://huggingface.co/Wan-AI/Wan2.1-T2V-14B/resolve/main/models_t5_umt5-xxl-enc-bf16.pth
2wget https://huggingface.co/DeepBeepMeep/Wan2.1/resolve/main/models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
3wget https://huggingface.co/Wan-AI/Wan2.1-T2V-14B/resolve/main/Wan2.1_VAE.pth
4wget https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/diffusion_models/wan2.1_t2v_1.3B_bf16.safetensors
5wget https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/diffusion_models/wan2.1_t2v_14B_bf16.safetensorswan_generate_video.py script with the appropriate parameters. Below are examples of how to generate videos using the Chinese_Children model.1python wan_generate_video.py --fp8 --task t2v-1.3B --video_size 480 832 --video_length 81 --infer_steps 20 \
2--save_path save --output_type both \
3--dit wan2.1_t2v_1.3B_bf16.safetensors --vae Wan2.1_VAE.pth \
4--t5 models_t5_umt5-xxl-enc-bf16.pth \
5--attn_mode torch \
6--lora_weight IM_ZH_outputs/IM_ZH_w1_3_lora-000010.safetensors \
7--lora_multiplier 1.0 \
8--prompt "烈日当空,细软的金沙被海风卷起细小的漩涡。一个赤脚男孩跪在沙滩上,用小铲子挖起湿沙,垒成城堡。"
91python wan_generate_video.py --fp8 --task t2v-1.3B --video_size 480 832 --video_length 81 --infer_steps 20 \
2--save_path save --output_type both \
3--dit wan2.1_t2v_1.3B_bf16.safetensors --vae Wan2.1_VAE.pth \
4--t5 models_t5_umt5-xxl-enc-bf16.pth \
5--attn_mode torch \
6--lora_weight IM_ZH_outputs/IM_ZH_w1_3_lora-000010.safetensors \
7--lora_multiplier 1.0 \
8--prompt "圆滚滚的棕毛小狗扑向青苔斑驳的石头,爪子在泥地上刨出小坑。它转眼又蹿回石头边转圈撒欢。"
9--fp8: Enable FP8 precision (optional).--task: Specify the task (e.g., t2v-1.3B).--video_size: Set the resolution of the generated video (e.g., 1024 1024).--video_length: Define the length of the video in frames.--infer_steps: Number of inference steps.--save_path: Directory to save the generated video.--output_type: Output type (e.g., both for video and frames).--dit: Path to the diffusion model weights.--vae: Path to the VAE model weights.--t5: Path to the T5 model weights.--attn_mode: Attention mode (e.g., torch).--lora_weight: Path to the LoRA weights.--lora_multiplier: Multiplier for LoRA weights.--prompt: Textual prompt for video generation.save_path directory.pip.