AnimeLoom/sakura-haruno

AnimeLoom — Sakura Haruno LoRA

Character LoRA for Sakura Haruno (Naruto), trained as part of the AnimeLoom anime character-consistency pipeline.

Two adapters are provided in this repo:

Folder	Base model	Rank	Steps	Images	Resolution
sdxl/	cagliostrolab/animagine-xl-3.1	32	800	18	512
sd15/	Lykon/dreamshaper-8	32	800	18	512

The SDXL adapter is the primary one used by AnimeLoom's identity-keyframe stage (SDXL + character LoRA + IP-Adapter). The SD 1.5 adapter is provided for compatibility with lighter inference pipelines (e.g. AnimateDiff workflows).

Trigger words

1girl, sakura haruno, pink hair, green eyes

Add booru-style descriptors as needed (e.g. red dress, forehead protector, smiling).

Usage — SDXL with PEFT / diffusers

import torch
from diffusers import StableDiffusionXLPipeline
from peft import PeftModel

pipe = StableDiffusionXLPipeline.from_pretrained(
    "cagliostrolab/animagine-xl-3.1",
    torch_dtype=torch.float16,
).to("cuda")

# AnimeLoom's training output is a PEFT adapter — load via PeftModel
pipe.unet = PeftModel.from_pretrained(
    pipe.unet,
    "AnimeLoom/sakura-haruno",
    subfolder="sdxl",
)

img = pipe(
    "1girl, sakura haruno, pink hair, green eyes, anime, "
    "masterpiece, best quality, absurdres",
    negative_prompt="blurry, low quality, deformed, extra fingers, 3d render",
    num_inference_steps=28,
    guidance_scale=6.5,
    height=1024, width=1024,
).images[0]
img.save("sakura.png")

Usage — SD 1.5 with diffusers

import torch
from diffusers import StableDiffusionPipeline

pipe = StableDiffusionPipeline.from_pretrained(
    "Lykon/dreamshaper-8",
    torch_dtype=torch.float16,
).to("cuda")

pipe.load_lora_weights(
    "AnimeLoom/sakura-haruno",
    subfolder="sd15",
    weight_name="pytorch_lora_weights.safetensors",
)

img = pipe(
    "1girl, sakura haruno, pink hair, green eyes, anime, masterpiece",
    num_inference_steps=28,
    guidance_scale=7.0,
).images[0]

Recommended weights & prompting

• LoRA scale: 0.85 - 1.15 (SDXL), 0.6 - 0.8 (SD 1.5)
• Pair with anime base models: Animagine XL 3.1, Counterfeit-V3.0, AnythingV5
• For face consistency in video, combine with IP-Adapter SDXL and Wan2.2-Animate face-lock — see the AnimeLoom pipeline.

AnimeLoom video pipeline integration

This LoRA is built to feed AnimeLoom's text-to-anime-video pipeline:

SDXL + this LoRA + IP-Adapter   →  identity keyframe (Phase 2)
        ↓
Wan2.2 I2V                       →  motion driving clip (Phase 3a)
        ↓
Wan2.2-Animate face-lock         →  face from keyframe pasted onto motion (Phase 3b)
        ↓
RIFE + Real-ESRGAN + GFPGAN      →  temporal/spatial upscale + face restore (Phase 4)
        ↓
Final 24fps anime video with consistent character identity across shots.

Limitations

• Anime-only. Photoreal prompts will degrade quality.
• InsightFace face-swap does not work on these outputs (it is photoreal-only). For identity rescue use IP-Adapter-FaceID-SDXL or CharacterFaceSwap.
• Trained on a small image set (18 images at 512 resolution); expect occasional drift on unusual angles, complex outfits, or non-canonical hair styles.
• The SDXL adapter was trained at 512 res — inference at 1024 works but very small details (hair strands, eye highlights) may be slightly less crisp than a 1024-trained adapter.

License

Released under OpenRAIL++ (openrail++), inheriting from the base model Animagine XL 3.1.

Related models

Part of the AnimeLoom character collection:

• AnimeLoom/sakura-haruno (this card)
• AnimeLoom/denji
• AnimeLoom/yuki-nagato

Citation

If you use this LoRA in research or production, please credit AnimeLoom and the base model authors (Cagliostro Lab for Animagine XL 3.1, Lykon for DreamShaper 8).

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Trained with PEFT as part of the AnimeLoom project.