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Reza2kn/visualears-fastconformer-fa-full-ab-litert-w4
visualears-fastconformer-fa-full-ab-litert-w4 is a automatic speech recognition model from Reza2kn. Use it when you need speech turned into text. It is set up for tflite. The card lists the license as apache-2.0.
LiteRT/TFLite weight-only 4-bit export of Reza2kn/visualears-fastconformer-fa-full-ab.
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From the Hugging Face model README
LiteRT/TFLite weight-only 4-bit export of Reza2kn/visualears-fastconformer-fa-full-ab.
FULLY_CONNECTED ops, regex Wrapper;[2-9], channelwiseThis artifact passed the earlier frame-level argmax gate, but it does not pass transcript parity.
| Check | Result |
|---|---|
| Frame-level CTC argmax parity vs PyTorch | 98.23% |
| Greedy CTC transcript parity vs PyTorch on 16 calibration items | 37.5% / 6 of 16 |
| Greedy CTC transcript parity vs LiteRT FP on 16 calibration items | 37.5% / 6 of 16 |
The earlier 98.23% number is frame-level CTC argmax token agreement, not "98% same final transcripts." For transcript-parity-sensitive use, this W4 artifact should be treated as failed.
This export takes precomputed log-mel features as processed_signal; it is not a full raw-audio-to-text pipeline by itself.
Best compressed LiteRT 4-bit attempt so far, but not a transcript-parity artifact. All-FC W4 compressed to 28.0% but failed at 96.51% frame argmax parity; safe FC+conv failed at 97.51% frame argmax parity.