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Update README.md #460

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Aug 18, 2024
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Update README.md #460

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Update README.md
hkfi Jul 17, 2024
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Merge branch 'main' into patch-1
guillaume-be Aug 18, 2024
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6 changes: 3 additions & 3 deletions README.md
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Expand Up @@ -177,8 +177,8 @@ installation instructions/support.

Most architectures (including encoders, decoders and encoder-decoders) are
supported. the library aims at keeping compatibility with models exported using
the [optimum](https://github.com/huggingface/optimum) library. A detailed guide
on how to export a Transformer model to ONNX using optimum is available at
the [Optimum](https://github.com/huggingface/optimum) library. A detailed guide
on how to export a Transformer model to ONNX using Optimum is available at
https://huggingface.co/docs/optimum/main/en/exporters/onnx/usage_guides/export_a_model
The resources used to create ONNX models are similar to those based on Pytorch,
replacing the pytorch by the ONNX model. Since ONNX models are less flexible
Expand All @@ -197,7 +197,7 @@ Note that the computational efficiency will drop when the `decoder with past`
file is optional but not provided since the model will not used cached past keys
and values for the attention mechanism, leading to a high number of redundant
computations. The Optimum library offers export options to ensure such a
`decoder with past` model file is created. he base encoder and decoder model
`decoder with past` model file is created. The base encoder and decoder model
architecture are available (and exposed for convenience) in the `encoder` and
`decoder` modules, respectively.

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