Translation
Transformers
PyTorch
nllb-moe
feature-extraction
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@@ -231,7 +231,7 @@ Safiyyah Saleem, Holger Schwenk, and Jeff Wang.
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  ## Training:
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  - The Expert Output Masking is used for training, which consists in droping the full contribution for some tokens. This corresponds to the following scheme:
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- ![EOM](https://drive.google.com/uc?id=1VNr3Ug5mQT4uFlvMDaTEyfg9rwbwGFsl/view?usp=sharing)
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  ## Generating with NLLB-MoE
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  The avalable checkpoints requires around 350GB of storage. Make sure to use `accelerate` if you do not have enough RAM on your machine.
 
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  ## Training:
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  - The Expert Output Masking is used for training, which consists in droping the full contribution for some tokens. This corresponds to the following scheme:
234
+ ![EOM](https://drive.google.com/uc?export=view&id=1VNr3Ug5mQT4uFlvMDaTEyfg9rwbwGFsl)
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  ## Generating with NLLB-MoE
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  The avalable checkpoints requires around 350GB of storage. Make sure to use `accelerate` if you do not have enough RAM on your machine.