From e5a4b39cb09539785f6ef25b8b2e84f072524a16 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Marcus=20Bl=C3=A4ttermann?= Date: Mon, 21 Nov 2022 12:45:00 +0100 Subject: [PATCH] Fix ESLint `react/no-unescaped-entities` --- website/src/templates/index.js | 2 +- website/src/templates/universe.js | 6 +-- website/src/widgets/landing.js | 50 ++++++++++++------------ website/src/widgets/quickstart-models.js | 4 +- 4 files changed, 31 insertions(+), 31 deletions(-) diff --git a/website/src/templates/index.js b/website/src/templates/index.js index 438e5b91e..25674e28e 100644 --- a/website/src/templates/index.js +++ b/website/src/templates/index.js @@ -112,7 +112,7 @@ const AlertSpace = ({ nightly, legacy }) => { )} {!isOnline && ( - But don't worry, your visited pages should be saved for you. + But don't worry, your visited pages should be saved for you. )} diff --git a/website/src/templates/universe.js b/website/src/templates/universe.js index 6db6d0fb2..14495b727 100644 --- a/website/src/templates/universe.js +++ b/website/src/templates/universe.js @@ -123,9 +123,9 @@ const UniverseContent = ({ content = [], categories, theme, pageContext, mdxComp )}
-

Found a mistake or something isn't working?

+

Found a mistake or something isn't working?

- If you've come across a universe project that isn't working or is + If you've come across a universe project that isn't working or is incompatible with the reported spaCy version, let us know by{' '} opening a discussion thread @@ -234,7 +234,7 @@ const Project = ({ data, components }) => ( )} {data.cran && (

)} diff --git a/website/src/widgets/landing.js b/website/src/widgets/landing.js index c842e155d..56eb1fdbc 100644 --- a/website/src/widgets/landing.js +++ b/website/src/widgets/landing.js @@ -75,15 +75,15 @@ const Landing = ({ data }) => { spaCy is designed to help you do real work — to build real products, or gather real insights. The library respects your time, and tries to avoid wasting it. - It's easy to install, and its API is simple and productive. + It's easy to install, and its API is simple and productive. - spaCy excels at large-scale information extraction tasks. It's written from the - ground up in carefully memory-managed Cython. If your application needs to + spaCy excels at large-scale information extraction tasks. It's written from + the ground up in carefully memory-managed Cython. If your application needs to process entire web dumps, spaCy is the library you want to be using. @@ -115,33 +115,33 @@ const Landing = ({ data }) => { spaCy Tailored Pipelines - Get a custom spaCy pipeline, tailor-made for your NLP problem by spaCy's - core developers. + Get a custom spaCy pipeline, tailor-made for your NLP problem by + spaCy's core developers.

@@ -166,7 +166,7 @@ const Landing = ({ data }) => {
Prodigy is an annotation tool so efficient that data scientists can do the annotation themselves, enabling a new level of rapid iteration. - Whether you're working on entity recognition, intent detection or image + Whether you're working on entity recognition, intent detection or image classification, Prodigy can help you train and evaluate your models faster. @@ -214,7 +214,7 @@ const Landing = ({ data }) => {

End-to-end workflows from prototype to production

- spaCy's new project system gives you a smooth path from prototype to + spaCy's new project system gives you a smooth path from prototype to production. It lets you keep track of all those{' '} data transformation, preprocessing and{' '} training steps, so you can make sure your project is always @@ -237,11 +237,11 @@ const Landing = ({ data }) => { small > spaCy v3.0 features all new transformer-based pipelines that - bring spaCy's accuracy right up to the current state-of-the-art - . You can use any pretrained transformer to train your own pipelines, and even - share one transformer between multiple components with{' '} - multi-task learning. Training is now fully configurable and - extensible, and you can define your own custom models using{' '} + bring spaCy's accuracy right up to the current{' '} + state-of-the-art. You can use any pretrained transformer to + train your own pipelines, and even share one transformer between multiple + components with multi-task learning. Training is now fully + configurable and extensible, and you can define your own custom models using{' '} PyTorch, TensorFlow and other frameworks. {

Benchmarks

- spaCy v3.0 introduces transformer-based pipelines that bring spaCy's + spaCy v3.0 introduces transformer-based pipelines that bring spaCy's accuracy right up to the current state-of-the-art. You can also use a CPU-optimized pipeline, which is less accurate but much cheaper to run. diff --git a/website/src/widgets/quickstart-models.js b/website/src/widgets/quickstart-models.js index af44788b5..c7f8086f4 100644 --- a/website/src/widgets/quickstart-models.js +++ b/website/src/widgets/quickstart-models.js @@ -93,7 +93,7 @@ const QuickstartInstall = ({ id, title, description, children }) => { import spacy - nlp = spacy.load("{pkg}") + nlp = spacy.load("{pkg}") import {pkg} @@ -102,7 +102,7 @@ const QuickstartInstall = ({ id, title, description, children }) => { nlp = {pkg}.load() - doc = nlp("{exampleText}") + doc = nlp("{exampleText}") print([