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Update README.md
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README.md
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@@ -37,7 +37,7 @@ We provide extensive evaluation results of SeamlessM4T-Medium and SeamlessM4T-La
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The SeamlessM4T models are currently available through the `seamless_communication` package. The `seamless_communication`
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package can be installed by following the instructions outlined here: [Installation](https://github.com/facebookresearch/seamless_communication/tree/main#installation).
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Once installed, a [`Translator`](https://github.com/facebookresearch/seamless_communication/blob/
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object can be instantiated to perform all five of the spoken langauge tasks. The `Translator` is instantiated with three arguments:
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1. **model_name_or_card**: SeamlessM4T checkpoint. Can be either `seamlessM4T_medium` for the medium model, or `seamlessM4T_large` for the large model
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2. **vocoder_name_or_card**: vocoder checkpoint (`vocoder_36langs`)
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The SeamlessM4T models are currently available through the `seamless_communication` package. The `seamless_communication`
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package can be installed by following the instructions outlined here: [Installation](https://github.com/facebookresearch/seamless_communication/tree/main#installation).
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Once installed, a [`Translator`](https://github.com/facebookresearch/seamless_communication/blob/main/src/seamless_communication/models/inference/translator.py#L50)
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object can be instantiated to perform all five of the spoken langauge tasks. The `Translator` is instantiated with three arguments:
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1. **model_name_or_card**: SeamlessM4T checkpoint. Can be either `seamlessM4T_medium` for the medium model, or `seamlessM4T_large` for the large model
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2. **vocoder_name_or_card**: vocoder checkpoint (`vocoder_36langs`)
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