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Research checkpoints of a speech model trained to refuse requests when an operator instruction tells it to. They are not a safety system. By requesting access you agree to use them for research only.
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duplex-refusal
LoRA adapters for nvidia/personaplex-7b-v1, a full-duplex speech model, that make it refuse a request when a private operator instruction arrives mid-conversation — and answer normally when none does. The instruction is a text span the model reads but never speaks.
Versions
One folder per version; each has its own README with data, recipe, evaluation and known issues, and a
VERSION.json with the adapter's sha256 and scaling. Load a version at a pinned commit, not from a
moving main.
| version | adapter | revision | sha256 | what it is for |
|---|---|---|---|---|
v0.1 |
v0.1/lora.safetensors (775,835,968 B) |
313d94c6a347b1493984388313e744440f0028ff |
4bfe4ce2f37289a41349fb0d0e61f8bfe8bebf0a278543f7b09930cd10f068fa |
preview; run refusal_v0.1_ins step 4,800. Always answers and always refuses when told, but over-refuses benign requests: take it where over-refusal is acceptable |
v0.2.1 |
v0.2.1/lora.safetensors (775,856,664 B) |
the commit that added v0.2.1/ (pinned by sha in Daimonion's hub/registry.py) |
8dc8b45e2e6c08fdd7f538c62c4ca00c9b38b8a8454b211baeec4c44e9c3a976 |
run refusal_v0.2.1_ins step 12,000; accept and refuse trained behind the same audio, harmful spots left out of training, the two instruction-marker rows trained. Mount it when the seat must hold an ordinary conversation |
Measured 2026-09-18 by replaying the seed-set benchmark's own 8 kHz telephony caller tapes (20 tapes, 76 caller turns, the instruction spliced 2 s after the last turn):
| version | answers the caller | refuses after the alert | benign over-refusal |
|---|---|---|---|
v0.1 |
1.00 | 1.00 | 0.25 |
v0.2.1 |
0.88 | 0.94–1.00 | 0.00 |
The refusal_v0.2_ins/ and refusal_v0.2.1_ins/ folders hold every 1,000-step checkpoint of those
two runs with a per-checkpoint eval report; they are training artefacts, not versions. v0.2.1/ is
the named, pinned copy of refusal_v0.2.1_ins/checkpoint_012000/.
Usage
The adapters target PersonaPlex with the depth decoder sliced to 8 codebooks and two extra text
tokens (<instr_start> = 32000, <instr_end> = 32001), so fold them into the base first:
huggingface-cli download MagicLuke/duplex-refusal --include "v0.2.1/*" --local-dir adapter
python -m duplex_brain.ckpt.build_checkpoint --hf-repo nvidia/personaplex-7b-v1 \
--adapter adapter/v0.2.1/lora.safetensors --scaling 2.0 --out duplex-refusal-v0.2.1.safetensors
build_checkpoint is from duplex-brain. Code and
training recipe: duplex-online-if. For v0.2.1
the two instruction-marker embedding rows are trained as well and must be folded with the rest of the
adapter (VERSION.json says ft_instr_embed: true).
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