DewiBrynJones
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Update README.md
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README.md
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@@ -25,8 +25,6 @@ transcriptions of Welsh language spontaneous speech [Banc Trawsgrifiadau Bangor
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ac well as recordings of read speach from [Welsh Common Voice version 18 (cv)](https://huggingface.co/datasets/techiaith/commonvoice_18_0_cy)
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for additional training.
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As such this model is suitable for more verbatim transcribing of spontaneous or unplanned speech.
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The Whisper large-v3-turbo pre-trained model is a finetuned version of a pruned Whisper large-v3. In other words, this model is the
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same model as [techiaith/whisper-large-v3-ft-btb-cv-cy](https://huggingface.co/techiaith/whisper-large-v3-ft-btb-cv-cy),
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except that the number of decoding layers have been reduced. As a result, the model is way faster, at the expense
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@@ -37,6 +35,8 @@ It achieves the following results on the [Banc Trawsgrifiadau Bangor'r test set]
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- WER: 30.27
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- CER: 11.14
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## Usage
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ac well as recordings of read speach from [Welsh Common Voice version 18 (cv)](https://huggingface.co/datasets/techiaith/commonvoice_18_0_cy)
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for additional training.
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The Whisper large-v3-turbo pre-trained model is a finetuned version of a pruned Whisper large-v3. In other words, this model is the
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same model as [techiaith/whisper-large-v3-ft-btb-cv-cy](https://huggingface.co/techiaith/whisper-large-v3-ft-btb-cv-cy),
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except that the number of decoding layers have been reduced. As a result, the model is way faster, at the expense
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- WER: 30.27
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- CER: 11.14
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As such this model is suitable for faster verbatim transcribing of spontaneous or unplanned speech.
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## Usage
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