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visualears-fastconformer-fa-full-ab-qat-w2-materialized
Reza2kn/visualears-fastconformer-fa-full-ab-qat-w2-materialized
visualears-fastconformer-fa-full-ab-qat-w2-materialized is a automatic speech recognition model from Reza2kn. Use it when you need speech turned into text. It is set up for nemo. The card lists the license as apache-2.0.
This repo contains the current 2-bit QAT materialized NeMo checkpoint from the VisualEars FastConformer Persian ASR quantization experiments.
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.nemo459 MB · 100%
At a glance
- Task
- Automatic Speech Recognition
- Library
- nemo
- License
- apache-2.0
- Access
- Public
- Created
- Jun 12, 2026
- Updated
- Jun 12, 2026
- SHA
- 4bb9ddfb
Base models
Model card
From the Hugging Face model README
VisualEars FastConformer FA Full AB - QAT W2 Materialized
This repo contains the current 2-bit QAT materialized NeMo checkpoint from the VisualEars FastConformer Persian ASR quantization experiments.
Important: this is a materialized float NeMo checkpoint, not a packed 2-bit deployment artifact yet. The selected QAT linear weights are projected to their 2-bit values and saved back into normal NeMo/torch tensors, so the file size is still close to the full precision .nemo.
Source
Base model: Reza2kn/visualears-fastconformer-fa-full-ab
Training run: onebit_cotraining_fast_no_urls_lower3_20260612_161154
Quantized modules: feed-forward linear layers in encoder layers 0-2, decoder/CTC/attention/convolution left unquantized.
VisualEars269 score
Default decoding:
| model | WER | CER |
|---|---|---|
| FP baseline | 32.64% | 13.30% |
| W2 materialized | 37.47% | 16.69% |
Forced CTC:
| model | WER | CER |
|---|---|---|
| FP baseline | 34.96% | 14.36% |
| W2 materialized | 40.65% | 17.78% |
This is useful as an experimental checkpoint, but it is not yet parity and not yet compressed/bit-packed.
- Task
- Automatic Speech Recognition
- Library
- nemo
- License
- apache-2.0
- Languages
- fa
- Created
- Jun 12, 2026
- Updated
- Jun 12, 2026