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@@ -32,7 +32,9 @@ model-index:
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  Fine-tuned facebook/wav2vec2-large-xlsr-53 on Hindi and Marathi using the OpenSLR SLR64 datasets. When using this model, make sure that your speech input is sampled at 16kHz.
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  ## Installation
 
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  pip install git+https://github.com/huggingface/transformers.git datasets librosa torch==1.7.0 torchaudio==0.7.0 jiwer
 
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  ## Eval dataset:
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  ```bash
@@ -99,7 +101,7 @@ import re
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  test = Dataset.from_csv('test.csv')
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- chars_to_ignore_regex = '[\\,\\?\\.\\!\\-\\;\\:\\"\\“\\%\\‘\\”\\�\\।]'
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  # Preprocessing the datasets.
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  # We need to read the audio files as arrays
@@ -139,7 +141,7 @@ import numpy as np
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  import re
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  from datasets import load_dataset
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- chars_to_ignore_regex = '[\\,\\?\\.\\!\\-\\;\\:\\"\\“\\%\\‘\\”\\�\\।]'
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  # Preprocessing the datasets.
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  # We need to read the audio files as arrays
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  Fine-tuned facebook/wav2vec2-large-xlsr-53 on Hindi and Marathi using the OpenSLR SLR64 datasets. When using this model, make sure that your speech input is sampled at 16kHz.
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  ## Installation
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+ ```bash
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  pip install git+https://github.com/huggingface/transformers.git datasets librosa torch==1.7.0 torchaudio==0.7.0 jiwer
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+ ```
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  ## Eval dataset:
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  ```bash
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  test = Dataset.from_csv('test.csv')
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+ chars_to_ignore_regex = '[\\\\,\\\\?\\\\.\\\\!\\\\-\\\\;\\\\:\\\\"\\\\“\\\\%\\\\‘\\\\”\\\\�\\\\।]'
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  # Preprocessing the datasets.
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  # We need to read the audio files as arrays
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  import re
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  from datasets import load_dataset
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+ chars_to_ignore_regex = '[\\\\,\\\\?\\\\.\\\\!\\\\-\\\\;\\\\:\\\\"\\\\“\\\\%\\\\‘\\\\”\\\\�\\\\।]'
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  # Preprocessing the datasets.
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  # We need to read the audio files as arrays