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README.md
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@@ -74,7 +74,10 @@ The model can be evaluated as follows on the zh-CN test data of Common Voice.
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Original CER calculation refer to https://huggingface.co/ctl/wav2vec2-large-xlsr-cantonese
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```python
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import torch
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import torchaudio
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@@ -114,7 +117,7 @@ processor = Wav2Vec2Processor.from_pretrained("ydshieh/wav2vec2-large-xlsr-53-ch
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model = Wav2Vec2ForCTC.from_pretrained("ydshieh/wav2vec2-large-xlsr-53-chinese-zh-cn-gpt")
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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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Original CER calculation refer to https://huggingface.co/ctl/wav2vec2-large-xlsr-cantonese
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```python
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#!pip install datasets==1.4.1
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#!pip install transformers==4.4.0
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#!pip install torchaudio
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#!pip install jiwer
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import torch
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import torchaudio
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model = Wav2Vec2ForCTC.from_pretrained("ydshieh/wav2vec2-large-xlsr-53-chinese-zh-cn-gpt")
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model.to("cuda")
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chars_to_ignore_regex = '[\\\\\\\\\\\\\\\\,\\\\\\\\\\\\\\\\?\\\\\\\\\\\\\\\\.\\\\\\\\\\\\\\\\!\\\\\\\\\\\\\\\\-\\\\\\\\\\\\\\\\;\\\\\\\\\\\\\\\\:"\\\\\\\\\\\\\\\\“\\\\\\\\\\\\\\\\%\\\\\\\\\\\\\\\\‘\\\\\\\\\\\\\\\\”\\\\\\\\\\\\\\\\�\\\\\\\\\\\\\\\\.\\\\\\\\\\\\\\\\⋯\\\\\\\\\\\\\\\\!\\\\\\\\\\\\\\\\-\\\\\\\\\\\\\\\\:\\\\\\\\\\\\\\\\–\\\\\\\\\\\\\\\\。\\\\\\\\\\\\\\\\》\\\\\\\\\\\\\\\\,\\\\\\\\\\\\\\\\)\\\\\\\\\\\\\\\\,\\\\\\\\\\\\\\\\?\\\\\\\\\\\\\\\\;\\\\\\\\\\\\\\\\~\\\\\\\\\\\\\\\\~\\\\\\\\\\\\\\\\…\\\\\\\\\\\\\\\\︰\\\\\\\\\\\\\\\\,\\\\\\\\\\\\\\\\(\\\\\\\\\\\\\\\\」\\\\\\\\\\\\\\\\‧\\\\\\\\\\\\\\\\《\\\\\\\\\\\\\\\\﹔\\\\\\\\\\\\\\\\、\\\\\\\\\\\\\\\\—\\\\\\\\\\\\\\\\/\\\\\\\\\\\\\\\\,\\\\\\\\\\\\\\\\「\\\\\\\\\\\\\\\\﹖\\\\\\\\\\\\\\\\·\\\\\\\\\\\\\\\\×\\\\\\\\\\\\\\\\̃\\\\\\\\\\\\\\\\̌\\\\\\\\\\\\\\\\ε\\\\\\\\\\\\\\\\λ\\\\\\\\\\\\\\\\μ\\\\\\\\\\\\\\\\и\\\\\\\\\\\\\\\\т\\\\\\\\\\\\\\\\─\\\\\\\\\\\\\\\\□\\\\\\\\\\\\\\\\〈\\\\\\\\\\\\\\\\〉\\\\\\\\\\\\\\\\『\\\\\\\\\\\\\\\\』\\\\\\\\\\\\\\\\ア\\\\\\\\\\\\\\\\オ\\\\\\\\\\\\\\\\カ\\\\\\\\\\\\\\\\チ\\\\\\\\\\\\\\\\ド\\\\\\\\\\\\\\\\ベ\\\\\\\\\\\\\\\\ャ\\\\\\\\\\\\\\\\ヤ\\\\\\\\\\\\\\\\ン\\\\\\\\\\\\\\\\・\\\\\\\\\\\\\\\\丶\\\\\\\\\\\\\\\\a\\\\\\\\\\\\\\\\b\\\\\\\\\\\\\\\\f\\\\\\\\\\\\\\\\g\\\\\\\\\\\\\\\\i\\\\\\\\\\\\\\\\n\\\\\\\\\\\\\\\\p\\\\\\\\\\\\\\\\t' + "\\\\\\\\\\\\\\\\']"
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resampler = torchaudio.transforms.Resample(48_000, 16_000)
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