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Boa Hancock (One Piece) - Classic Red Outfit

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bf16 SafeTensor

boa_hancock_red_v6-41.safetensors

BF16, good balance • 175.11 MB

Verified:

Type
LoRA
Stats

129

52

38

Reviews
Published

Oct 12, 2026

Base Model

Anima

Hash
AutoV2
C80B6CD5FF

The Anima Model is licensed by CircleStone Labs LLC. Copyright CircleStone Labs LLC. IN NO EVENT SHALL CIRCLESTONE LABS LLC BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH USE OF THIS MODEL.

Built on NVIDIA Cosmos

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Model Overview

This LoRA is trained on Boa Hancock's red outfit from the Amazon Lily arc. The dataset is curated using official One Piece anime frames alongside selected images sourced from Pinterest.

Eye Tagging System

To fix poorly-drawn and inconsistent eyes in frames, four distinct, canon-sourced iris designs were extracted from high-detail anime frames and applied across the dataset.


Instead of using one generic eye type, four different cornea designs were applied to match specific moods and the pre-timeskip style.

  • nelvoth iris: Gives Boa a beautiful look; best suited for cute, in-love, and normal expressions.


  • blue eyes: Standard pre-timeskip design with simpler shading.


  • dark blue eyes, black pupils: Sourced primarily from the One Piece: Stampede movie, best suited for cold, neutral, and slightly angry expressions.


  • light blue eyes, black pupils: Best suited for shocked, terrified, and intense angry expressions.

Snake Earrings (ss_earrings)

To generate the earrings, use the tag ss_earrings.

Usage Instructions:

  • When prompting for ss_earrings, add pearl earrings to your negative prompt. The base model sometimes attempts to generate pearl earrings simultaneously, causing structural deformation.

  • To generate the character without earrings, remove ss_earrings from your positive prompt and place ss_earrings in your negative prompt.

  • The snake earrings in standard anime frames are frequently inconsistent and lack fine detail. To correct this, a clean canon design from high-quality frames was used to redraw and standardize the earrings across the dataset.


Outfit Generation & Tags

Topwear

  • Trigger Tags: veskarn crop top, flower pattern on long sleeves, white cape, epaulettes.


  • Sleeve Details: The veskarn crop top sleeves feature base snake-scale patterns on the forearms alongside a floral emblem with circular petals. The flower pattern on long sleeves tag specifically controls this floral emblem. If you only want the snake-scale design without the floral pattern, add long sleeves to your positive prompt and place flower pattern on long sleeves in your negative prompt, as the model often struggles to render this floral emblem accurately.

  • Outfit Swapping: The bottom section of the crop top has concept bleed. To generate entirely different topwear, you must add veskarn crop top and pink belt with golden buckle on crop top to your negative prompt.

  • Chest Pattern Correction: The patterns around the breasts were inconsistent in the original anime frames. The dataset was manually edited to replace them with a consistent, refined design across all images.

Bottomwear

  • Trigger Tags: mirsolen sarong with flower patterns, light purple waist sash.

    • Tip: When prompting for the sarong, add bad flower patterns on sarong, deformed flower patterns on sarong to your negative prompt, as the model often struggles to render these pattern details cleanly.

  • Outfit Swapping: To generate custom skirts or pants, add mirsolen sarong with flower patterns and light purple waist sash to your negative prompt to fully remove the default lower design.

Salome the Snake

To generate Boa Hancock's pet snake, use the base trigger tag Salome the snake. The dataset uses specific sentence-style tags to control Salome's position, expression, and interaction with Hancock.

Positional & Interaction Tags:

  • Salome is coiled up: Generates Salome resting in a coiled position.

  • Salome is behind Boa Hancock: Places Salome in the background.

  • Boa Hancock is resting on Salome like a throne: Add throne to the negative prompt.

  • Boa Hancock is standing on Salome the snake

  • Salome is in dynamic movement: Generates Salome actively moving rather than resting.

Expression & Detail Tags:

  • Salome has open mouth

  • Salome has closed mouth

  • Salome has clenched teeth

  • Salome is angry

The Claw of the Celestial Dragons

  • Trigger Tags: red circular tattoo with three triangles at top and one triangle below the circle, back tattoo

Signature Pose: Mero Mero Mellow

  • Base Pose (No Effects): To generate the hand gesture without any glowing hearts, use the tags thumbs on top heart hands, outstretched arms, foreshortening.

    • Tip: Add heart to negative prompt.

  • Frontal Attack: To generate the hearts shooting directly at the screen, use the tags thumbs on top heart hands, heart hands releasing multiple glowing pink hearts towards viewer, outstretched arms, foreshortening.

  • Side Attack: To generate the character shooting the hearts sideways, use the tags thumbs on top heart hands, heart hands releasing multiple glowing pink hearts to the side, outstretched arms, foreshortening.

Looking Down Pose

  • Trigger Tags: head back, face hidden, leaning back, pointing down, outstretched arm, hand on own hip, foreshortening.

Expressions & Other Poses

  • Younger Appearance: Use the tag aged down to give Boa Hancock a younger look.


  • Hair Flip: Use the tag hair flip to generate her running her hand through her hair. This tag works exceptionally well when combined with dynamic pose.


  • Comedic Angry Face: Use the tags triangular blank eyes, shaded face to recreate her specific anime-style angry expression with blank white eyes.


  • Intense Shadowed Face: Use the tags shaded face, black shaded eyes.


  • Wet Look: Use the tags wet, wet hair to render her drenched hair and skin appearance.

Training Details & Parameters

  • Base Model: Anima Base v1.0

  • Dataset Size: 194 images (1 repeat)

  • Trained Version Checkpoint: Epoch 41 / 3,977 steps

  • Hardware & Batch Size: 2x GPU (Effective Batch Size 2: 97 steps per epoch)

  • Training Resolution: 1152 × 1152 (with bucketing enabled)

  • Network Rank / Alpha: Dim 64 / Alpha 32 (Trained UNet only)

  • Learning Rate: 0.0002 (Cosine scheduler, AdamW8bit optimizer)

  • Recommended LoRA Weight: 1.0

📌 Custom LoRA Commissions Open!

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