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@@ -24,7 +24,7 @@ model-index:
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  value: 37.36
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  ---
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- # Wav2Vec2-Large-XLSR-53-Irish
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  Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) in Estonian using the [Common Voice](https://huggingface.co/datasets/common_voice)
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  When using this model, make sure that your speech input is sampled at 16kHz.
@@ -85,7 +85,7 @@ processor = Wav2Vec2Processor.from_pretrained("manandey/wav2vec2-large-xlsr-esto
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  model = Wav2Vec2ForCTC.from_pretrained("manandey/wav2vec2-large-xlsr-estonian")
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  model.to("cuda")
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- chars_to_ignore_regex = '[\,\?\.\!\-\;\:\"\“\%\‘\”\�\|\।\–\’\']'
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  resampler = torchaudio.transforms.Resample(48_000, 16_000)
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  # Preprocessing the datasets.
 
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  value: 37.36
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  ---
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+ # Wav2Vec2-Large-XLSR-53-Estonian
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  Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) in Estonian using the [Common Voice](https://huggingface.co/datasets/common_voice)
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  When using this model, make sure that your speech input is sampled at 16kHz.
 
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  model = Wav2Vec2ForCTC.from_pretrained("manandey/wav2vec2-large-xlsr-estonian")
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  model.to("cuda")
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+ chars_to_ignore_regex = '[\\,\\?\\.\\!\\-\\;\\:\\"\\“\\%\\‘\\”\\�\\|\\।\\–\\’\\']'
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  resampler = torchaudio.transforms.Resample(48_000, 16_000)
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  # Preprocessing the datasets.