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Arturo Wolff | Anima

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Updated: Sep 16, 2026

characterawffnima

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132.24 MB

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Type
LoRA
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Published

Sep 16, 2026

Base Model

Anima

Training
Steps: 1,525
Epochs: 10
Usage Tips
Strength: 1
Hash
AutoV2
3968166BDF
Trigger Words
awffnima
default creator card background decoration
Reactions - 564

564

Followers - 54

54

Likes - 2

2

Created on Civitai

License:

Anima

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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🐺 ARTURO WOLFF β€” Character LoRA for Anima

A character LoRA built to reproduce Arturo Wolff β€”me.

This is my Arturo Wolff character LoRA, trained natively for Anima.

Arturo is my personal character, online identity, and the central figure behind most of the artwork I make. Over time, his design has accumulated a lot of little visual decisions that are easy to describe individually but surprisingly difficult to reproduce as a coherent whole: the proportions, facial structure, scruffy silhouette, color separation, eyes, ears, tail, posture, expressions, and that permanently exhausted-looking rockstar energy.

The purpose of this LoRA is to compress all of that into a reusable character representation.

The goal is:

Arturo should remain Arturo even when everything else changes.


β—† WHO IS ARTURO?

Arturo Wolff is a slim anthropomorphic wolf with a deliberately recognizable visual identity:

  • Gray fur

  • Dark / black countershading

  • Black ears

  • Red eyes

  • Scruffy fur

  • Large pointed wolf ears

  • Digitigrade anatomy

  • Large, fluffy two-tone wolf tail

  • Lean proportions rather than an exaggerated muscular build

  • Naturally tired-looking eyes and facial structure

  • Usually carrying some degree of dry, sleepy, unimpressed, or rockstar-like expression

That last part is particularly important.

The tired appearance is part of the character design.

During dataset captioning, some of those identity-defining facial characteristics were intentionally left implicit rather than constantly being tagged as separate concepts. The idea was to encourage the network to associate them with Arturo himself, instead of learning that Arturo is simply a generic wolf who optionally receives a tired_eyes modifier.

However, depending on the checkpoint, these tags might be necessary:

β€œtired eyes, bags under eyes, notched ear, scruffy fur, slim, anthro, furry”


β—† TRIGGER / IDENTITY

Primary identity token

awffnima

For most prompts, I recommend treating the character token as the anchor and then describing the scene normally.

You do not necessarily need to exhaustively reconstruct Arturo from tags every single time.

That defeats part of the purpose of a character LoRA.

A basic prompt can be as simple as:

awffnima, solo, black jacket, standing in a convenience store at night, looking at viewer

Then add pose, clothing, expression, framing, environment, style, artist tags, etc. as needed.

If a particular generation begins drifting, explicit anatomical or color descriptors can be added to reinforce the relevant feature.


β—† EXAMPLE PROMPTS

Simple Character Test

awffnima, standing, full body, looking at viewer, relaxed posture, black shirt, jeans, simple interior

A useful test because there is very little for the prompt to hide behind.


β—† PROMPTING PHILOSOPHY

I generally recommend describing what you want Arturo to be doing, rather than spending half of the prompt repeatedly explaining who Arturo is.

For example:

Instead of:

gray wolf, black ears, red eyes, gray fur, black fur, fluffy tail, two-tone tail, scruffy hair...

try:

awffnima, sitting sideways on a diner booth, one arm resting over the backrest, holding a coffee cup, looking out the window

Then reinforce individual physical traits only when necessary.

A good identity LoRA should perform some of the descriptive work for you.


β—† LoRA STRENGTH

It was meant to work only at 1.0 but you might have to up the antee in some cases.


β—† BASE MODEL

Architecture: Anima
Training Base: CircleStone Labs β€” Anima Base v1.0
Model Format: Anima LoRA
Implementation: Diffusers
Network Module: networks.lora

This was trained against Anima Base, which is the correct member of the Anima family for LoRA training rather than training directly against one of the more opinionated aesthetic/distilled variants.

The LoRA can be experimented with on compatible Anima models and finetunes, but behavior may vary depending on how heavily the target checkpoint alters the original model.


β—† TRAINING DATA

Training images: 61*50
Regularization images: 0
Dataset repeats: 10
Training resolution: 1024 Γ— 1024


β—† NETWORK CONFIGURATION

LoRA Rank / Network Dimension: 32
Network Alpha: 32


β—† OPTIMIZATION

Optimizer: AdamW 8-bit
Weight Decay: 0.0001

Learning Rate: 0.0001
Model / Transformer LR: 0.0001
Text Encoder LR: 0

LR Scheduler: Constant


β—† CAPTION REGULARIZATION

Caption Dropout: 0.05 / 5%

A small amount of caption dropout was used during training.

Conceptually, caption dropout discourages the network from relying perfectly on every caption element being present on every iteration. For character training, this can help reduce brittle relationships between the character and incidental tags in the dataset.

The objective is not just:

specific token combination = specific training picture

but a more generalized internal representation of the character.


β—† PRECISION & MEMORY CONFIGURATION

Training Precision: BF16
Gradient Checkpointing: Enabled
Latent Caching: Disabled
Full FP16: Disabled
Noise Offset: 0

The exported LoRA itself contains:

896 BF16 tensors

with approximately:

69.27 million stored tensor elements

and a file size of approximately:

132.3 MiB


β—† TRAINING ENVIRONMENT

The embedded training metadata reports:

Training software: ai-toolkit
ai-toolkit version: 0.12.14
Training controller: Civitai Spine Controller
GPU architecture: Ada
Reported VRAM: 24 GB

The file also contains the standard SafeTensors training metadata necessary for model identification and reproducibility.


β—† WHAT I WANT FROM THIS MODEL

  1. For me to create content of my fursona

  2. For others to create fanart of my fursona

  3. Validation


β—† ABOUT THE CHARACTER

Arturo exists at the intersection of my artwork, music, online identity, and the larger collection of characters and projects I've built around him.

Arturo is also generally portrayed as a womanizer, depressed, whimsy, and other stuff I can't share here.

You are absolutely allowed to take him out of that context tho.

Put the wolf somewhere stupid.


β—† FINAL NOTES

The model is meant to be used, pushed around, mixed with styles, given weird outfits, placed into environments completely outside of the original dataset, and generally stress-tested.

If you make something interesting with him, I genuinely want to see it.

🐺

Have fun.