karume-anima-turbo

Deprecated (2026-09-03). This repository is retired and will not be updated. Upstream now publishes Turbo as an official checkpoint, so Karume ships it as the anima-turbo-v1.1 model of hdae/karume-anima (the default model there; the LoRA-baked variant here is superseded). @karume/models 0.8.0 removed the ANIMA_TURBO_CURRENT pin — use ANIMA_CURRENT. The files stay in place so that revisions pinned by earlier package versions keep resolving.

Anima Turbo — Karume

What is this

A distribution that bakes Anima Turbo LoRA v0.2 into circlestone-labs/Anima-Base-v1.0-Diffusers and converts it into the WebGPU inference runtime Karume's container format (a single safetensors file = weights + a graph JSON embedded in __metadata__). Runs as-is in the browser and in Deno.

• A few-step distillation (from the LoRA) tuned for 8 steps / guidance 1.
• Not readable by diffusers (it's a different container with an embedded graph); the reader is a pipeline that implements anima/1.
• Exporter used for the conversion: karume/0.7.0. The distribution manifest is karume.json (karume/4).

Baked-in LoRA

Folded into the weights — not distributed as a separate file.

• Name: Anima Turbo LoRA v0.2
• Author: circlestone_labs (same author as the base model)
• Source: https://civitai.com/models/2560840?modelVersionId=2979642
• File: anima-turbo-lora-v0.2.safetensors
• sha256: 1b55e40bdb1d0e5a78cb498f245fccfdaae97823265db957d2aabdcf4cd3caf1

Permissions listed on the source page (as of retrieval):

• allowNoCredit: true
• allowCommercialUse: Image / RentCivit / Rent
• allowDerivatives: true
• allowDifferentLicense: true

(These are the LoRA page's own permissions. The merged distribution in this repository stays under the CircleStone Non-Commercial License — see the License section below.)

License

The weights derive from the CircleStone Anima base model and stay under the CircleStone Non-Commercial License (non-commercial use only). This repository ships LICENSE.md (the full license text) and NOTICE.md (this attribution plus the list of modifications).

The CircleStone Model is licensed by CircleStone Labs LLC under the CircleStone Non-Commercial License. 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.

• Baked-in LoRA: the official Anima Turbo LoRA v0.2 (source), folded into the weights at export.
• This is not an official product of CircleStone Labs LLC, and it is not endorsed, approved or validated by CircleStone Labs LLC.

Models

model selects one of these; omitted, it is anima-turbo. quant defaults to that model's own default quant.

Usage

import { AnimaPipeline, encodePng } from "jsr:@karume/models";

using pipeline = await AnimaPipeline.fromPretrained({
  repo: "hdae/karume-anima-turbo",
  // Pin a commit for reproducible builds — without it you track `main`, and a future
  // repo update (renamed files, new manifest format) may break your app.
  // Copy the full hash from this repo's "Files and versions" tab:
  // revision: "<full commit sha>",
}, {
  // model: "anima-turbo", // default — available: anima-turbo
  // quant: "f16+dit8-a8-attn8-s16", // default — available: f16 / f16+dit4 / f16+dit4-attn8-s16 / f16+dit8 / f16+dit8-a8 / f16+dit8-a8-attn8 / f16+dit8-a8-attn8-s16 / f16-c16
});

const image = await pipeline.generate({
  prompt: "1girl, solo, long hair, blue eyes, school uniform, masterpiece",

  // steps: 8, // default — the baked-in LoRA is distilled for few-step sampling
  // Resolution — non-square is fine; each side on a 16 px grid, between 512 and 2048 px:
  // resolution: { width: 1024, height: 1024 }, // default

  // Classifier-free guidance runs a second (uncond) branch — twice the work per step.
  // It is skipped at guidanceScale 1, where a negativePrompt is refused rather than
  // silently ignored, so the two lines below only make sense together:
  // guidanceScale: 5,
  // negativePrompt: "low quality, worst quality, blurry, bad anatomy, jpeg artifacts",

  seed: 42, // same seed + same request → same image
});

const png = await encodePng(image.data, image.width, image.height);
await Deno.writeFile("anima.png", png);

Weights are fetched once and cached (verified against karume.json's size / sha256). You can also load from a local directory (AnimaPipeline.fromAssets).

Model: anima-turbo

Files

Only the first 16 hex digits of the sha256 are shown (the full value and size live in karume.json — verify against that at the fetch layer). Dtype labels use the runtime's storage dtype vocabulary (f16 / i8 / i4), not the fp16 spelling common elsewhere in the ecosystem. A path under shared/ is one this model shares byte for byte with another model in this repository (it is fetched and cached once). A row that names another repository is fetched from that repository at the pinned commit shown — those bytes are identical to this model's own, so they are not stored here a second time.

Quants

If no quant is given, it runs as f16+dit8-a8-attn8-s16 (this model's recommended default). In a quant name, dit is the transformer component.

Defaults

Any knob not passed to generate() is filled in from the manifest's defaults.

• steps: 8
• guidanceScale: 1
• resolution: 1024 × 1024
• negativePrompt: low quality, worst quality, blurry, bad anatomy, jpeg artifacts

At guidance 1, the second CFG branch is skipped, so the negative prompt is not used (it only takes effect once guidance is raised).