Update README.md
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README.md
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config: Ukrainian P&C
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split: test
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args:
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language:
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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 (
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<style>
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img {
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@@ -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/
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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/
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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/
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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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```
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