# Lora of Tokawa Sakiko in Wan2.1Train and inference in [DiffSynth-Studio](<a target="_blank" rel="ugc" href="https://github.com/modelscope/DiffSynth-Studio/tree/main/diffsynth">https://github.com/modelscope/DiffSynth-Studio/tree/main/diffsynth</a>).Base model: [Wan2.1-T2V-1.3B](<a target="_blank" rel="ugc" href="https://huggingface.co/Wan-AI/Wan2.1-T2V-1.3B">https://huggingface.co/Wan-AI/Wan2.1-T2V-1.3B</a>)Dataset: [togawa_sakiko_bangdreamitsmygo](<a target="_blank" rel="ugc" href="https://huggingface.co/datasets/CyberHarem/togawa_sakiko_bangdreamitsmygo">https://huggingface.co/datasets/CyberHarem/togawa_sakiko_bangdreamitsmygo</a>)## Inference<pre><code>import torch

from diffsynth import ModelManager, WanVideoPipeline, save_video, VideoData

model_manager = ModelManager(torch_dtype=torch.bfloat16, device="cpu")

model_manager.load_models([

 "models/Wan-AI/Wan2.1-T2V-1.3B/diffusion_pytorch_model.safetensors",

 "models/Wan-AI/Wan2.1-T2V-1.3B/models_t5_umt5-xxl-enc-bf16.pth",

 "models/Wan-AI/Wan2.1-T2V-1.3B/Wan2.1_VAE.pth",

])

model_manager.load_lora("models/lightning_logs/version_2/checkpoints/epoch=9-step=1250.ckpt", lora_alpha=1.0)

pipe = WanVideoPipeline.from_model_manager(model_manager, device="cuda")

pipe.enable_vram_management(num_persistent_param_in_dit=None)

video = pipe(

 prompt="1girl,solo,long_hair,blush,smile,bangs,shirt,ribbon,closed_mouth,hair_ribbon,yellow_eyes,grey_hair,sidelocks,outdoors,day,blunt_bangs,sailor_collar,blurry,official_alternate_costume,tree,looking_to_the_side,black_ribbon,depth_of_field,blurry_background,looking_away,portrait,light_blush,bush,brown_shirt,official_alternate_hairstyle",

 negative_prompt="bad_quality,low_quality,low_res,low_resolution,low_definition,low_definition_video,low_definition_image,low_definition_video_image,low_definition_video_image_quality,low_definition_video_image_quality_video,low_definition_video_image_quality_video_image,low_definition_video_image_quality_video_image_video,low_definition_video_image_quality_video_image_video_image",

 num_inference_steps=50,

 seed=0, tiled=True

)

save_video(video, "video.mp4", fps=30, quality=5)</code></pre>

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