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svlandeg 2020-08-27 19:56:52 +02:00
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10
website/docs/api/architectures.md
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@ -323,11 +323,11 @@ for details and system requirements.
Load and wrap a transformer model from the
[HuggingFace `transformers`](https://huggingface.co/transformers) library. You
can any transformer that has pretrained weights and a PyTorch implementation.
The `name` variable is passed through to the underlying library, so it can be
either a string or a path. If it's a string, the pretrained weights will be
downloaded via the transformers library if they are not already available
locally.
can use any transformer that has pretrained weights and a PyTorch
implementation. The `name` variable is passed through to the underlying library,
so it can be either a string or a path. If it's a string, the pretrained weights
will be downloaded via the transformers library if they are not already
available locally.
In order to support longer documents, the
[TransformerModel](/api/architectures#TransformerModel) layer allows you to pass