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  ## beto2beto-mlsum
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- This model was trained using Amazon SageMaker and the new Hugging Face Deep Learning container.
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- For more information look at:
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- - [🤗 Transformers Documentation: Amazon SageMaker](https://huggingface.co/transformers/sagemaker.html)
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- - [Example Notebooks](https://github.com/huggingface/notebooks/tree/master/sagemaker)
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- - [Amazon SageMaker documentation for Hugging Face](https://docs.aws.amazon.com/sagemaker/latest/dg/hugging-face.html)
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- - [Python SDK SageMaker documentation for Hugging Face](https://sagemaker.readthedocs.io/en/stable/frameworks/huggingface/index.html)
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- - [Deep Learning Container](https://github.com/aws/deep-learning-containers/blob/master/available_images.md#huggingface-training-containers)
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  ## Hyperparameters
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  {
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  "dataset_config": "es",
 
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  ## beto2beto-mlsum
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+ This model was trained on the Spanish section of MLSum: https://paperswithcode.com/sota/abstractive-text-summarization-on-mlsum.
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  ## Hyperparameters
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  {
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  "dataset_config": "es",