Thanabordee/AudioLaya-poc
audio-classification model by Thanabordee
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Model card & documentation
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Trainable delta weights for an English-only proof-of-concept that classifies call audio as legitimate or spam directly from audio, with no ASR on the inference path. Whisper and Laya stay frozen and are not redistributed here — these files contain only the parameters that were trained. Whisper's decoder is never called on this path. Each checkpoint is a dict with experiment, epoch, validationmacrof1, trainablestate, trainableparametercount, and modelids. In A only the projector is in trainablestate; in B it also holds Laya's type embedding, decision Transformer, and option scorer. The semantic variants add spam cross-entropy + 0.05 × InfoNCE(projected audio, paired transcript) at temperature 0.07. Transcripts are training-time supervision only — inference reads raw audio. These weights require the code in ThanabordeeN/AudioLaya: The first run also downloads openai/whisper-small.en and convaiinnovations/laya. Same 282-call internal test split (146 Harper legitimate, 136 FTC spam; 576 chunks), chunk probabilities averaged per original call: On 14 legitimate…
Read the full model card ↗ · Preview checked 2026-11-05T22:50:46.978Z
Inside the original model card — Document outline
- Audio-Laya — Direct Speech-to-Decision PoC (checkpoints)
- Files
- Usage
- Results
- Limitations — read before using
- License
- Citation
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Documentation belongs to its respective authors. Reported project/model license: mit. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.
Model overview
Thanabordee/AudioLaya-poc is a audio-classification model repository published by Thanabordee on Hugging Face. The source reports the pytorch library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- audio-classification
- Library
- pytorch
- Recent downloads (30 days)
- 0
- Cumulative likes
- 0
- Hugging Face trending score
- 0
- Reported safetensors parameters
- Not reported
- Architecture
- Not reported
- License
- mit
- Access
- Not gated by Hugging Face
- Created
- 2026-09-24T06:21:33.000Z
- Last modified
- 2026-09-24T06:22:20.000Z
Compatibility and lineage
Reported languages: en
Reported base models: openai/whisper-small.en, convaiinnovations/laya
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-09-24T06:37:32.927Z. Daily imports are snapshots, not real-time monitoring.
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