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aimeri/spoomplesmaxx-mockingbird-36B-GGUF overview

spoomplesmaxx mockingbird 36B — GGUF static Static GGUF quants of spoomplesmaxx mockingbird 36B https://huggingface.co/aimeri/spoomplesmaxx mockingbird 36B , t…

ggufroleplaycreative-writingtext-generationenbase_model:aimeri/spoomplesmaxx-mockingbird-36Bbase_model:quantized:aimeri/spoomplesmaxx-mockingbird-36Blicense:apache-2.0endpoints_compatibleregion:usconversational

Runs locally from ~16.41 GB disk (24 GB VRAM class GPUs with llama.cpp / guIDE).

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Pipeline
text-generation
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Repository Files & Downloads

4 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
spoomplesmaxx-mockingbird-36B.Q3_K_M.ggufGGUFGGUF16.41 GBDownload
spoomplesmaxx-mockingbird-36B.Q4_K_M.ggufGGUFGGUF20.27 GBDownload
spoomplesmaxx-mockingbird-36B.Q4_K_S.ggufGGUFGGUF19.27 GBDownload
spoomplesmaxx-mockingbird-36B.Q5_K_M.ggufGGUFGGUF23.84 GBDownload

Model Details

Model IDaimeri/spoomplesmaxx-mockingbird-36B-GGUF
Authoraimeri
Pipelinetext-generation
Licenseapache-2.0
Base modelaimeri/spoomplesmaxx-mockingbird-36B
Last modified2026-08-26T01:09:28.000Z

Model README

---

license: apache-2.0

base_model: aimeri/spoomplesmaxx-mockingbird-36B

library_name: gguf

pipeline_tag: text-generation

tags:

- roleplay

- creative-writing

language:

- en

---

spoomplesmaxx-mockingbird-36B — GGUF (static)

Static GGUF quants of

spoomplesmaxx-mockingbird-36B,

the first of the mimids. Weighted/imatrix quants (calibrated on the model's

own training corpus) live in

-i1-GGUF;

prefer those at 3–4 bit if your runtime supports them.

| Quant | Size | Notes |

|---|---|---|

| Q3_K_M | ~18 GB | the 18GB target; fine with a good card |

| Q4_K_S | ~21 GB | |

| Q4_K_M | ~22 GB | recommended balance |

| Q5_K_M | ~26 GB | closest to bf16 behavior |

The seed-native chat template is embedded in the GGUF metadata — llama.cpp,

koboldcpp, and LM Studio pick it up automatically.

Sampling — read this part

temperature 1.0 · top_p 0.9 · repeat_penalty 1.0 (OFF)

> ⚠ Never use repetition, presence, or frequency penalties.

> The template ends every message with <seed:eos>; context-wide penalties

> suppress that token, the model stops ending its turns, and generation

> degenerates into the base model's untrained Chinese vocabulary. Many

> frontend presets default repeat_penalty to 1.05–1.1 — set it back to 1.0.

> Use DRY or XTC if you want extra anti-repetition; both leave special

> tokens alone.

Usable temperature window is ~0.95–1.05: lower loops verbatim, higher frays.

Full details, corpus notes, and training story on the

main model card.

mimids 01 · Apache 2.0

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