Couplet

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Couplet

Instruction-tuned chat model (~268M) — Couplet family

A ~268M hybrid GDN-2 + GQA model, supervised fine-tuned for chat

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What this is

Couplet is the supervised fine-tuned (SFT) chat checkpoint for the Couplet family.

• Base (pretrain): kerzgrr/Couplet-base
• Larger successor to kerzgrr/Monostich-2
• Architecture: hybrid Gated DeltaNet-2 + gated GQA

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Training

Pretrain → SFT

Chat template (ChatML)

<|begin_of_text|><|im_start|>system
{system}<|im_end|>
<|im_start|>user
{user}<|im_end|>
<|im_start|>assistant
{assistant}<|im_end|>

Generation prompt ends at <|im_start|>assistant\n.

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Model Architecture

Same TinyGDN hybrid as the base (267,857,662 parameters):

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IFEval

Official 541-prompt Google IFEval scorer, zero-shot ChatML, greedy decoding (temperature=0, max_new_tokens=1280):

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Install & run

pip install torch safetensors tokenizers huggingface_hub
hf download kerzgrr/Couplet inference.py --local-dir .
python inference.py --prompt "What is the capital of France?"

inference.py auto-downloads weights/tokenizer/tiny_gdn/ and auto-installs pinned flash-linear-attention (Windows applies Hub patches). Git is required on PATH.

Interactive chat:

python inference.py

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Limitations

• Scale: at ~268M parameters this is a research / edge model, not a frontier system
• Instruction following: IFEval shows useful but limited constraint following; verify critical outputs
• Dependency: requires flash-linear-attention; not GGUF / llama.cpp compatible today

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Model family

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Citation

@misc{couplet2026,
  title={Couplet: A 268M Hybrid GDN-2 + GQA Chat Model},
  author={kerzgrr},
  year={2026},
  url={https://huggingface.co/kerzgrr/Couplet}
}

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Acknowledgments

• flash-linear-attention (Gated DeltaNet-2)
• HuggingFaceTB/smoltalk
• NousResearch/Hermes-3-Dataset
• Base: kerzgrr/Couplet-base

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A couplet is a pair of lines — compact, connected, and complete.

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