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@@ -31,6 +31,9 @@ It achieves the following results on the evaluation set:
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  ## usage
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  an example of aggregating summaries from chunks of a long document:
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  ```py
@@ -66,6 +69,7 @@ res = pipe(
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  print(res[0]["generated_text"])
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  ```
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  ## Training procedure
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  ### Training hyperparameters
 
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  ## usage
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+ > [!TIP]
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+ > BART supports several speedups for inference on GPU, including [flash-attention2](https://huggingface.co/docs/transformers/perf_infer_gpu_one#flashattention-2) and [torch SDPA](https://huggingface.co/docs/transformers/perf_infer_gpu_one#pytorch-scaled-dot-product-attention)
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  an example of aggregating summaries from chunks of a long document:
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  ```py
 
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  print(res[0]["generated_text"])
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  ```
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  ## Training procedure
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  ### Training hyperparameters