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@@ -28,7 +28,7 @@ See [this notebook](https://colab.research.google.com/github/patrickvonplaten/no
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  ### Limitations and bias
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- This model was pre-trained with audio samples whose maximum length was 60 seconds so this model most likely works the best for quite short audios of similar length. However, you can try this model with a lot longer audios too and see how it works. If you encounter out of memory errors with very long audio files you can use the audio chunking method introduced in [this blog post](https://huggingface.co/blog/asr-chunking).
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  The model was pre-trained on the data from the [Lahjoita puhetta (Donate Speech) corpus](https://link.springer.com/article/10.1007/s10579-022-09606-3) so this model might have biases towards colloquial Finnish.
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  ### Limitations and bias
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+ This model was pre-trained with audio samples whose maximum length was 60 seconds so this model most likely works the best for short audios of similar length. However, you can try this model with a lot longer audios too and see how it works. If you encounter out of memory errors with very long audio files you can use the audio chunking method introduced in [this blog post](https://huggingface.co/blog/asr-chunking).
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  The model was pre-trained on the data from the [Lahjoita puhetta (Donate Speech) corpus](https://link.springer.com/article/10.1007/s10579-022-09606-3) so this model might have biases towards colloquial Finnish.
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