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README.md
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@@ -59,8 +59,28 @@ Our AI models are designed and/or optimized to run on NVIDIA GPU-accelerated sys
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## How to Use the Model
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## Software Integration:
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**Runtime Engine(s):**
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## How to Use the Model
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The model is available for use in the NeMo toolkit [2], and can be used as a pre-trained checkpoint for inference.
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### Automatically load the model
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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.EncDecFrameClassificationModel.from_pretrained(model_name="frame_vad_multilingual_marblenet_v2.0.nemo")
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```
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### Perform VAD Inference
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```bash
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python <NEMO_ROOT>/examples/asr/speech_classification/frame_vad_infer.py \
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--config-path="../conf/vad" \
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--config-name="frame_vad_infer_postprocess.yaml" \
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vad.model_path=<Path to .nemo file from which model should be instantiated> \
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input_manifest=<Path of manifest file of evaluation data, where audio files should have unique names> \
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prepare_manifest.auto_split=True \
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prepare_manifest.split_duration=7200 \
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vad.parameters.shift_length_in_sec=0.02 \
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out_manifest_filepath=<Path of output manifest file>
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```
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## Software Integration:
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**Runtime Engine(s):**
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