nsnet-dse-artifacts

claroche1/nsnet-dse-artifacts

nsnet-dse-artifacts is a machine learning model from claroche1. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.

Reproduction artefacts for the nsnetdse toolchain: four int8 / DRUM speech-enhancement engines (NSNet2 dense, Monarch sparse NSNet2, ConvFSENet, Gated ConvFSENet) and the DRUM approximate-multiplier design-space explo…

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Updated Jul 10, 2026

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At a glance

License: mit
Access: Public
Created: Jul 10, 2026
Updated: Jul 10, 2026
SHA: 88190ce3

Model card

From the Hugging Face model README

nsnet_dse — run artefacts

Reproduction artefacts for the nsnet_dse toolchain: four int8 / DRUM speech-enhancement engines (NSNet2 dense, Monarch sparse NSNet2, ConvFSENet, Gated ConvFSENet) and the DRUM approximate-multiplier design-space exploration built on them.

The code repo is self-contained except for these artefacts (trained checkpoints, result outputs, and a bit-exact engine snapshot), which are gitignored. The repo's common/hf_artifacts.ensure_artifact() pulls the checkpoints from here automatically on a fresh clone, so git clone → reproduce works with no manual downloads.

Dataset (not hosted here): JacobLinCool/VoiceBank-DEMAND-16k — 11,572 train / 824 test utterances at 16 kHz.

Layout

checkpoints/     trained weights (the load-bearing artefacts)
  nsnet2_rt_gain8_best.pt          NSNet2 FP32 (input-gain-8 recipe)
  convfsenet_qf_causal_best.pt     ConvFSENet FP32 (also the gated warm-start)
  convfsenet_gated_causal_best.pt  Gated ConvFSENet FP32
  monarch_full_g_best.pt           Monarch FP32 source (eco8 cp_monarch_full/g_best)
  monarch_full_qat.npz             Monarch packed int8 QAT weights (the deployed model)
results/         per-utt CSVs, paired-CI txt, train metrics/logs, and the
                 sensitivity/defensible/clamp-decomposition JSONs + a repro log
engines/         bit-exact snapshot: per-model int8 header (*.h) + compiled *_bin
MANIFEST.json    file -> {sha256, bytes, producer script, consumers}

Verified headline numbers (full 824-utt VoiceBank-DEMAND test, real C engine)

model	int8 PESQ-WB	STOI	reference
NSNet2 (dense)	2.8116	0.9354	FP32 recipe, input-gain 8
Monarch (sparse, QAT)	2.7443	0.9309	FP32 ref 2.8374
ConvFSENet	2.7556	0.9179	FP32 ref 2.7672
Gated ConvFSENet (50-utt)	2.9047	0.9233	FP32 ref 2.8852

(Reproduced 2026-07-10, full 824-utt test unless noted; matches docs/GATE-RESULTS.md.)

Numbers and the paired A/B comparisons are recorded in results/REPRODUCE-<date>.md and cross-checked against docs/GATE-RESULTS.md in the code repo. Energy percentages in the code repo are multiplier-array-only with unverified per-op constants — read them as a relative ranking, not system energy.

Reproduce

git clone <code-repo> && cd nsnet_dse
pip install -r requirements.txt
# checkpoints auto-download from this repo on first use, or grab them all:
hf download claroche1/nsnet-dse-artifacts --local-dir artifacts
cd nsnet2 && bash build.sh && python3 reproduce_eval.py     # etc. per model

Provenance caveats

Do not mix checkpoints / engines / pipeline vintages — see docs/RESULTS-PROVENANCE.md in the code repo. monarch_full_qat.npz is the authoritative deployed Monarch model; monarch_full_g_best.pt is its FP32 source. *_last.pt optimizer-state snapshots and the unreferenced convfsenet_snapshot.pt are intentionally omitted.

License: mit
Created: Jul 10, 2026
Updated: Jul 10, 2026