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README.md
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language: sw
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datasets:
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- ALFFA
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metrics:
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- wer
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# Wav2Vec2-Large-XLSR-53-Swahili
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Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on Swahili using the
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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 script used for training can be found [here]https://colab.research.google.com/drive/1_RL6TQv_Yiu_xbWXu4ycbzdCdXCqEQYU?usp=sharing
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---
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language: sw
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datasets:
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- [ALFFA](http://www.openslr.org/25)
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- [Gamayun](https://gamayun.translatorswb.org/download/gamayun-5k-english-swahili/)
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- [IWSLT](https://iwslt.org/2021/low-resource)
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metrics:
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- wer
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# Wav2Vec2-Large-XLSR-53-Swahili
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Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on Swahili using the following datasets:
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- [ALFFA](http://www.openslr.org/25/),
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- [Gamayun](https://gamayun.translatorswb.org/download/gamayun-5k-english-swahili/)
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- [IWSLT](https://iwslt.org/2021/low-resource)
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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 script used for training can be found [here](https://colab.research.google.com/drive/1_RL6TQv_Yiu_xbWXu4ycbzdCdXCqEQYU?usp=sharing)
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