Dark-Scarlett-v1.0-QAT-26B-A4B-Voice
Scarlett's voice, fitted to QAT-derived GGUFs. Same idea as the main voice, correct math for QAT heads.
This carries ReadyArt/Dark-Scarlett-v1.0-26B-A4B as a delta against the standard instruct, matched to Google's QAT checkpoint (google/gemma-4-26B-A4B-it-qat-q4_0-unquantized). If your GGUF is built from QAT weights, use this one; otherwise the standard voice is the exact fit.
QAT + Scarlett
Two separate things, stacked:
Google's QAT trains the model to survive quantization — 54% less perplexity drop at Q4_0 versus standard post-training quantization (Google Developers Blog).
Scarlett changes how it writes. In our test, the Scarlett delta fused onto a QAT-Q4_0 head moved diction 96% with zero comprehension cost (single probe — see the Voice tool repo).
If you already run a QAT GGUF, this variant keeps the QAT foundation intact instead of overwriting it with standard-instruct weights.
Two steps
# 1. Get the voice tool (one-time): https://huggingface.co/Wiself/voice
python3 voice.py path
# 2. Cast onto your QAT-derived GGUF
voice cast ./gemma-4-26b-a4b-it-qat-q4_0-Q4_0.gguf voice.safetensors --out ./voiced/gemma-4-26b-a4b-qat-scarlett.gguf
Append --speak to force the voice through output.weight (invented if the target lacks it and geometry survives; GGUF only).
Run it:
llama serve -m ./voiced/gemma-4-26b-a4b-qat-scarlett.gguf --jinja
No QAT finetune was needed. No extra model was downloaded. Your model, darker voice, less quantization loss.
Why the QAT-matched variant exists
The QAT checkpoint's lm_head weights differ slightly from the standard instruct's (that's the point of QAT — the weights learned to live with quantization). This voice is cast as a delta against the normal google/gemma-4-26B-A4B-it (voice − base where base is the standard instruct, not QAT). When you later do delta + QAT_head → Q8_0, you add Scarlett's voice to the QAT head — correct math, matched foundation.
| Your GGUF is built from | Use |
|---|---|
google/gemma-4-26B-A4B-it (standard) | Scarlett voice |
google/gemma-4-26B-A4B-it-qat-q4_0-unquantized | this voice |
The abliterated case
The most popular QAT-adjacent models are abliterated/uncensored variants. We tested this exact pairing class (Scarlett-delta → QAT-Q4_0 head):
- Direct cast risks loops on heavily modified targets — repetitive output, unusable.
- Delta cast — clean output, no loops, Scarlett phrasing intact, diction moved 96% with zero comprehension cost.
On abliterated targets, the delta path is the default (base is the normal instruct — correct math):
voice delta voice.safetensors --base google/gemma-4-26B-A4B-it
voice cast ./model.gguf delta-voice.safetensors --out ./voiced/model.gguf
Why it works: a delta carries only the difference from the base head, so the shift to MoE routing is minimal. Full story in the Voice tool card.
What's inside
voice.safetensors— the voice delta (voice − base), source dtype preserved, arch-derived shape[262144, 2816], ~1.5 GBvoice.json— metadata: source, dtype, shape, base
Confirm after download: voice info voice.safetensors → [262144, 2816] (delta marker present).
Compatibility
| Target | Works? |
|---|---|
| QAT-derived Gemma 4 26B A4B GGUFs (any quant) | ✅ primary target |
| Abliterated QAT variants | ✅ via the delta path above |
| Standard (non-QAT) 26B A4B GGUFs | ✅ works, but the Scarlett voice is the exact match |
| Gemma 4 other sizes / non-Gemma | ❌ shape mismatch |
Notes
- Sampler tips from the source card: Top-P 0.92, temp 1.0, no frequency/presence penalty.
- Usage terms carry over: personal use only, 18+, you accept full responsibility for outputs — see the source card before sharing voiced models.
- Casting quantizes only the head to Q8_0 (near-lossless); every other tensor is byte-copied — your QAT weights stay QAT weights.
References & Credits
- Voice source: ReadyArt/Dark-Scarlett-v1.0-26B-A4B — LoRA r32, 2 epochs, 12,211 prompts (dataset: GECFDO; fine-tuning: FrenzyBiscuit).
- QAT: Google Developers Blog — checkpoint
google/gemma-4-26B-A4B-it-qat-q4_0-unquantized, Gemma terms. - Tool: Voice — lift a voice, cast it onto any compatible GGUF.