From 733114bdd91b707209956e521a6b423f2154ce72 Mon Sep 17 00:00:00 2001 From: Madeesh Kannan Date: Mon, 9 May 2022 19:44:14 +0200 Subject: [PATCH] `training.md`: Fix typos (#10775) --- website/docs/usage/training.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/website/docs/usage/training.md b/website/docs/usage/training.md index f46f0052b..5e064b269 100644 --- a/website/docs/usage/training.md +++ b/website/docs/usage/training.md @@ -247,7 +247,7 @@ a consistent format. There are no command-line arguments that need to be set, and no hidden defaults. However, there can still be scenarios where you may want to override config settings when you run [`spacy train`](/api/cli#train). This includes **file paths** to vectors or other resources that shouldn't be -hard-code in a config file, or **system-dependent settings**. +hard-coded in a config file, or **system-dependent settings**. For cases like this, you can set additional command-line options starting with `--` that correspond to the config section and value to override. For example, @@ -730,7 +730,7 @@ with the name of the respective [registry](/api/top-level#registry), e.g. `@spacy.registry.architectures`, and a string name to assign to your function. Registering custom functions allows you to **plug in models** defined in PyTorch or TensorFlow, make **custom modifications** to the `nlp` object, create custom -optimizers or schedules, or **stream in data** and preprocesses it on the fly +optimizers or schedules, or **stream in data** and preprocess it on the fly while training. Each custom function can have any number of arguments that are passed in via the