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  # Wav2vec 2.0 large-voxpopuli-sv-swedish
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- Finetuned version of Facebooks [VoxPopuli-sv large](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) model using NST and Common Voice data. WER for NST + Common Voice test set (2% of total sentences) is **5.19%**. WER for Common Voice test set is **17.38%**.
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  When using this model, make sure that your speech input is sampled at 16kHz.
 
 
 
 
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  ## Usage
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  The model can be used directly (without a language model) as follows:
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  ```python
 
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  ---
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  # Wav2vec 2.0 large-voxpopuli-sv-swedish
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+ Finetuned version of Facebooks [VoxPopuli-sv large](https://huggingface.co/facebook/wav2vec2-large-sv-voxpopuli) model using NST and Common Voice data. Evalutation without a language model gives the following: WER for NST + Common Voice test set (2% of total sentences) is **5.19%**, WER for Common Voice test set is **17.38%**.
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  When using this model, make sure that your speech input is sampled at 16kHz.
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+ ## Training
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+ The model was trained for 80000 updates
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  ## Usage
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  The model can be used directly (without a language model) as follows:
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  ```python