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Update README.md

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  1. README.md +4 -4
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@@ -76,7 +76,7 @@ The code will automatically normalize your audio (i.e., resampling + mono channe
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  First of all, please install tranformers and SpeechBrain with the following command:
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  ```
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- pip install speechbrain transformers==4.28.0
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  ```
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  Please notice that we encourage you to read our tutorials and learn more about
@@ -91,17 +91,17 @@ import torch
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  enh_model = Separator.from_hparams(
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  source="speechbrain/noisy-whisper-resucespeech",
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- savedir='pretrained_models/noisy-whisper-resucespeech',
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  hparams_file="enhance.yaml"
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  )
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  asr_model = WhisperASR.from_hparams(
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  source="speechbrain/noisy-whisper-resucespeech",
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- savedir="pretrained_models/noisy-whisper-resucespeech",
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  hparams_file="asr.yaml"
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  )
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  # For custom file, change the path accordingly
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- est_sources = enh_model.separate_file(path='example_rescuespeech16k.wav')
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  pred_words, _ = asr_model(est_sources[:, :, 0], torch.tensor([1.0]))
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  ```
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  ### Inference on GPU
 
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  First of all, please install tranformers and SpeechBrain with the following command:
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  ```
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+ pip install speechbrain
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  ```
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  Please notice that we encourage you to read our tutorials and learn more about
 
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  enh_model = Separator.from_hparams(
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  source="speechbrain/noisy-whisper-resucespeech",
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+ savedir='pretrained_models/noisy-whisper-rescuespeech',
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  hparams_file="enhance.yaml"
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  )
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  asr_model = WhisperASR.from_hparams(
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  source="speechbrain/noisy-whisper-resucespeech",
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+ savedir="pretrained_models/noisy-whisper-rescuespeech",
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  hparams_file="asr.yaml"
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  )
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  # For custom file, change the path accordingly
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+ est_sources = enh_model.separate_file(path='speechbrain/noisy-whisper-resucespeech/example_rescuespeech16k.wav')
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  pred_words, _ = asr_model(est_sources[:, :, 0], torch.tensor([1.0]))
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  ```
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  ### Inference on GPU