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@@ -54,9 +54,7 @@ The translation process for the ARC_Challenge_Swahili dataset involved two main
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  1. The initial translation from English to Swahili was performed using the SeamlessM4TModel translation model.
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  The following parameters were used for the translation:
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- ''' python
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-
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  inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True, max_length=1024).to(device)
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  outputs = model.generate(**inputs, tgt_lang=dest_lang)
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  translation = tokenizer.batch_decode(outputs, skip_special_tokens=True)
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- '''
 
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  1. The initial translation from English to Swahili was performed using the SeamlessM4TModel translation model.
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  The following parameters were used for the translation:
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+ ```python
 
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  inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True, max_length=1024).to(device)
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  outputs = model.generate(**inputs, tgt_lang=dest_lang)
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  translation = tokenizer.batch_decode(outputs, skip_special_tokens=True)