SubMaroon/Kanimus-26B-A4B-FFT-heretic-GGUF overview
Kanimus 26B A4B FFT heretic v4 QK LoRA Merge An experimental Dark Roleplay model created by manually merging QK projections via task arithmetic from a Claude O…
Runs locally from ~15.64 GB disk (16 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| v4_animus_qk_lora-Q4_K_M.gguf | GGUF | Q4_K_M | 15.64 GB | Download |
Model Details
Model README
---
base_model: Vortex5/Gemma-4-26B-A4B-Animus-V14.1-FFT-heretic
language:
- en
- ru
library_name: transformers
tags:
- mergekit
- task_arithmetic
- gemma
- gemma4
- moe
- roleplay
- russian
- english
- gguf
- quantized
license: gemma
---
Kanimus-26B-A4B-FFT-heretic (v4 QK-LoRA Merge)
An experimental Dark Roleplay model created by manually merging QK projections via task-arithmetic from a Claude Opus distillation, followed by the integration of a stylistic LoRA on top of the Animus-heretic base.
Architecture and Methodology
The model is built upon Gemma 4 26B A4B. The merge arithmetic was executed in FP32, with the final weights saved in bfloat16.
Step 1: QK Injection (Task Arithmetic)
A manual task-arithmetic injection was applied strictly to the Attention Query and Key projections. Formula used:
W_final = W_animus + α * (W_opus - W_unsloth)
Reference models:
- Parent Opus:
unsloth/gemma-4-26B-A4B-it - Target Opus:
TeichAI/gemma-4-26B-A4B-it-Claude-Opus-Distill-v2
Separate α coefficients were applied for a controlled attention shift (respecting QK-norm):
- α_sliding_q = 0.50
- α_sliding_k = 0.50
- α_global_q = 0.50
- α_global_k = 0.25 (halved to mitigate KV-injection collapse on long contexts)
Post-merge Invariant: All non-QK tensors (including MoE router, shared MLP, embeddings, and norms) remain bitwise equal to the original Animus-heretic base. This was verified via torch.equal during assembly.
Step 2: LoRA Bake
The stylistic LoRA SubMaroon/Dark-Goetia-26B-A4B-LoRA-v4 was baked directly into the model weights.
- Method:
set_scale("default", 0.20)->merge_and_unload(safe_merge=True) - Effective weight: 0.40 * BA (accounting for alpha/r = 2).
Usage and Recommendations
The model is designed for English and Russian Roleplay. It maintains scene logic, exhibits high NPC initiative, and operates within a dark, atmospheric writing style.
Recommended Sampling:
- Temperature: 0.7 - 0.8
- min_p: 0.05 - 0.1
- Repetition penalty: 1.05 - 1.10
Available Versions
- BF16: Full-precision version (~53 GB).
- GGUF Q4_K_M.
License
Distributed under the Gemma license. Usage is subject to the terms of the original Google models and the respective distillates.
Acknowledgements
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Source: Hugging Face · Compare models