license: apache-2.0
base_model: Reza2kn/visualears-fastconformer-fa-full-ab
language:
- fa
tags:
- automatic-speech-recognition
- nemo
- fastconformer
- qat
- persian
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.