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hlm-micro-keyword-v1-speechcommands
qriton/hlm-micro-keyword-v1-speechcommands
hlm-micro-keyword-v1-speechcommands is a audio classification model from qriton. Use it for the audio classification task on the model card, and read the license before you ship it in a product. It is set up for pytorch. The card lists the license as apache-2.0.
HLM-Micro Keyword Spotting v1 is a compact polynomial-Hopfield keyword spotter trained on the Google Speech Commands V2 12-class TinyML-style subset.
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.pt750 KB · 99%
At a glance
- Task
- Audio Classification
- Library
- pytorch
- License
- apache-2.0
- Access
- Public
- Created
- Jul 13, 2026
- Updated
- Jul 13, 2026
- SHA
- 986e0f92
Datasets
Model card
From the Hugging Face model README
HLM-Micro Keyword Spotting v1 - Speech Commands
HLM-Micro Keyword Spotting v1 is a compact polynomial-Hopfield keyword spotter trained on the Google Speech Commands V2 12-class TinyML-style subset.
Results
| Field | Value |
|---|---|
| Parameters | 184,449 |
| Classes | 12 |
| Reported best validation accuracy | 92.09% |
| Final validation accuracy | 92.01% |
| Best checkpoint | epoch 6 of 8 |
Classes: yes, no, up, down, left, right, on, off, stop, go, _silence_, _unknown_.
This is a realistic small keyword-spotting result, not a state-of-the-art accuracy claim. The test split is intentionally not claimed here.
Files
| File | Purpose |
|---|---|
model.pt | Sanitized model-only PyTorch checkpoint |
config.json | Public architecture, task, classes, and metric metadata |
metrics.jsonl | Training/evaluation metrics from the local run |
Intended Use
- Research on compact keyword spotting.
- TinyML and edge-audio experiments.
- Baseline for adding replayable audit metadata to edge classifiers.
Limitations
- Metric reported here is validation accuracy, not final held-out test accuracy.
- Not optimized with the full augmentation/training recipe used by top keyword-spotting systems.
- Not a wake-word product or production speech interface.
- Task
- Audio Classification
- Library
- pytorch
- License
- apache-2.0
- Created
- Jul 13, 2026
- Updated
- Jul 13, 2026