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PyTorch spelling

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svlandeg 2020-09-09 16:27:21 +02:00
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website/docs/usage/layers-architectures.md
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@ -228,7 +228,7 @@ Thinc allows you to [wrap models](https://thinc.ai/docs/usage-frameworks)
written in other machine learning frameworks like PyTorch, TensorFlow and MXNet
using a unified [`Model`](https://thinc.ai/docs/api-model) API.
For example, let's use Pytorch to define a very simple Neural network consisting
For example, let's use PyTorch to define a very simple Neural network consisting
of two hidden `Linear` layers with `ReLU` activation and dropout, and a
softmax-activated output layer.
@ -274,7 +274,7 @@ In the above example, we have combined our custom PyTorch model with a character
embedding layer defined by spaCy.
[CharacterEmbed](/api/architectures#CharacterEmbed) returns a `Model` that takes
a `List[Doc]` as input, and outputs a `List[Floats2d]`. To make sure that the
wrapped Pytorch model receives valid inputs, we use Thinc's
wrapped PyTorch model receives valid inputs, we use Thinc's
[`with_array`](https://thinc.ai/docs/api-layers#with_array) helper.
As another example, you could have a model where you use PyTorch just for the
@ -284,7 +284,7 @@ consideration for those parts of the network.
## Custom models for trainable components {#custom-models}
To use our custom model including the Pytorch subnetwork, all we need to do is
To use our custom model including the PyTorch subnetwork, all we need to do is
register the architecture. The full example then becomes:
```python