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sudo apt-get update && sudo apt-get install cbm git-lfs ffmpeg1git clone https://huggingface.co/svjack/Yato_wan_2_1_1_3_B_text2video_lora
2cd Yato_wan_2_1_1_3_B_text2video_lora1pip 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 Yato model.1python wan_generate_video.py --fp8 --task t2v-1.3B --video_size 480 832 --video_length 81 --infer_steps 50 \
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 Yato_outputs/Yato_w1_3_lora-000010.safetensors \
7--lora_multiplier 1.0 \
8--prompt "In the style of Noragami , The video features a series of close-up shots of an animated character with black hair and blue eyes. The character is eating a burger."
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101python wan_generate_video.py --fp8 --task t2v-1.3B --video_size 480 832 --video_length 81 --infer_steps 50 \
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 Yato_outputs/Yato_w1_3_lora-000010.safetensors \
7--lora_multiplier 1.0 --seed 77 \
8--prompt "In the style of Noragami , The video features a series of close-up shots of an animated character with black hair and blue eyes. The character carry money in a wallet at home"
91python wan_generate_video.py --fp8 --task t2v-1.3B --video_size 480 832 --video_length 81 --infer_steps 50 \
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 Yato_outputs/Yato_w1_3_lora-000010.safetensors \
7--lora_multiplier 1.0 \
8--prompt "In the style of Noragami , The video features a series of close-up shots of an animated character with black hair and blue eyes. the character shade from the sun with an umbrella outdoor."1python wan_generate_video.py --fp8 --task t2v-1.3B --video_size 480 832 --video_length 81 --infer_steps 50 \
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 Yato_outputs/Yato_w1_3_lora-000010.safetensors \
7--lora_multiplier 1.0 --seed 57 \
8--prompt "In the style of Noragami , The video features a series of close-up shots of an animated character with black hair and blue eyes. the character is sleep on the bed"
91[1] anime style, In the style of Noragami: 这个片段展示了,在校园内, 暗蓝暮色中，蓝发少年斜倚斑驳木门，指尖划过袖口白纹，围巾末端悬停半空，眉间蹙起一缕未解的阴霾。
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3[2] anime style, In the style of Noragami: 这个片段展示了,镜头一闪, 蓝发少年面对黑色的男人影子，黑色男人在蓝发少年面前一闪而过， 他骤然攥紧围巾褶皱，背景随动作加深，眼底浮起星火般的决意，袖口条纹在暗处灼然生光。
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5[3] anime style, In the style of Noragami: 这个片段展示了, 蓝发少年迅速跳向高空，随着镜头在下面照向腾空的少年,少年忽仰首直视虚空， scarf扬起如残月弧线，身后木纹扭曲成漩涡，蓝瞳倒映出无形之刃的寒芒。
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7[4] anime style, In the style of Noragami: 这个片段展示了, 天空迅速变暗, 蓝发少年位于天空的当中，背景为青白的月光, 在白月光下,最终他垂眸轻笑，指尖抵住门框旧伤，所有情绪敛入围巾阴影，唯余袖间白纹如斩破黑暗的刀痕。--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.