change the model in the text description to match code and model card. (#4)

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- change the model in the text description to match code and model card. (4ba95a1c9d5389bd957c37d142bc2d19b5122b32)

Co-authored-by: Pinzhen Chen <pinzhenchen@users.noreply.huggingface.co>

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README.md +1 -1

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@@ -235,7 +235,7 @@ Safiyyah Saleem, Holger Schwenk, and Jeff Wang.
 The avalable checkpoints requires around 350GB of storage. Make sure to use `accelerate` if you do not have enough RAM on your machine.
 While generating the target text set the `forced_bos_token_id` to the target language id. The following
-example shows how to translate English to French using the *facebook/nllb-200-distilled-600M* model.
 Note that we're using the BCP-47 code for French `fra_Latn`. See [here](https://github.com/facebookresearch/flores/blob/main/flores200/README.md#languages-in-flores-200)
 for the list of all BCP-47 in the Flores 200 dataset.

 The avalable checkpoints requires around 350GB of storage. Make sure to use `accelerate` if you do not have enough RAM on your machine.
 While generating the target text set the `forced_bos_token_id` to the target language id. The following
+example shows how to translate English to French using the *facebook/nllb-moe-54b* model.
 Note that we're using the BCP-47 code for French `fra_Latn`. See [here](https://github.com/facebookresearch/flores/blob/main/flores200/README.md#languages-in-flores-200)
 for the list of all BCP-47 in the Flores 200 dataset.