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@@ -44,14 +44,14 @@ model-index:
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  config: Ukrainian P&C
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  split: test
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  args:
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- language: uk
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  metrics:
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  - name: Test WER P&C
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  type: wer
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  value: 6.92
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  ---
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- # NVIDIA FastConformer-Hybrid Large (uk)
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  <style>
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  img {
@@ -83,7 +83,7 @@ The model is available for use in the NeMo toolkit [3], and can be used as a pre
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  ```python
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  import nemo.collections.asr as nemo_asr
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- asr_model = nemo_asr.models.EncDecHybridRNNTCTCBPEModel.from_pretrained(model_name="nvidia/stt_uk_fastconformer_hybrid_large_pc")
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  ```
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  ### Transcribing using Python
@@ -101,14 +101,14 @@ asr_model.transcribe(['2086-149220-0033.wav'])
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  Using Transducer mode inference:
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  ```shell
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  python [NEMO_GIT_FOLDER]/examples/asr/transcribe_speech.py
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- pretrained_name="nvidia/stt_uk_fastconformer_hybrid_large_pc"
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  audio_dir="<DIRECTORY CONTAINING AUDIO FILES>"
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  ```
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  Using CTC mode inference:
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  ```shell
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  python [NEMO_GIT_FOLDER]/examples/asr/transcribe_speech.py
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- pretrained_name="nvidia/stt_uk_fastconformer_hybrid_large_pc"
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  audio_dir="<DIRECTORY CONTAINING AUDIO FILES>"
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  decoder_type="ctc"
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  ```
 
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  config: Ukrainian P&C
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  split: test
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  args:
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+ language: ua
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  metrics:
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  - name: Test WER P&C
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  type: wer
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  value: 6.92
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  ---
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+ # NVIDIA FastConformer-Hybrid Large (ua)
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  <style>
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  img {
 
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  ```python
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  import nemo.collections.asr as nemo_asr
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+ asr_model = nemo_asr.models.EncDecHybridRNNTCTCBPEModel.from_pretrained(model_name="nvidia/stt_ua_fastconformer_hybrid_large_pc")
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  ```
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  ### Transcribing using Python
 
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  Using Transducer mode inference:
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  ```shell
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  python [NEMO_GIT_FOLDER]/examples/asr/transcribe_speech.py
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+ pretrained_name="nvidia/stt_ua_fastconformer_hybrid_large_pc"
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  audio_dir="<DIRECTORY CONTAINING AUDIO FILES>"
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  ```
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  Using CTC mode inference:
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  ```shell
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  python [NEMO_GIT_FOLDER]/examples/asr/transcribe_speech.py
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+ pretrained_name="nvidia/stt_ua_fastconformer_hybrid_large_pc"
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  audio_dir="<DIRECTORY CONTAINING AUDIO FILES>"
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  decoder_type="ctc"
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  ```