Remove MDX imports

This commit is contained in:
Marcus Blättermann 2022-11-17 17:17:26 +01:00
parent 888a1f4c60
commit 84db6ea20f
No known key found for this signature in database
GPG Key ID: A1E1F04008AC450D
17 changed files with 0 additions and 81 deletions

View File

@ -3,6 +3,4 @@ title: Library Architecture
next: /api/architectures next: /api/architectures
--- ---
import Architecture101 from 'usage/101/_architecture.mdx'
<Architecture101 /> <Architecture101 />

View File

@ -16,8 +16,6 @@ menu:
> For more details on how to use trained pipelines with spaCy, see the > For more details on how to use trained pipelines with spaCy, see the
> [usage guide](/usage/models). > [usage guide](/usage/models).
import QuickstartModels from 'widgets/quickstart-models.js'
<QuickstartModels id="quickstart" /> <QuickstartModels id="quickstart" />
## Package naming conventions {id="conventions"} ## Package naming conventions {id="conventions"}

View File

@ -44,8 +44,6 @@ enough, JSX components can be used.
## Logo {id="logo",source="website/src/images/logo.svg"} ## Logo {id="logo",source="website/src/images/logo.svg"}
import { Logos } from 'widgets/styleguide'
If you would like to use the spaCy logo on your site, please get in touch and If you would like to use the spaCy logo on your site, please get in touch and
ask us first. However, if you want to show support and tell others that your ask us first. However, if you want to show support and tell others that your
project is using spaCy, you can grab one of our project is using spaCy, you can grab one of our
@ -55,8 +53,6 @@ project is using spaCy, you can grab one of our
## Colors {id="colors"} ## Colors {id="colors"}
import { Colors, Patterns } from 'widgets/styleguide'
<Colors /> <Colors />
### Patterns ### Patterns
@ -65,8 +61,6 @@ import { Colors, Patterns } from 'widgets/styleguide'
## Typography {id="typography"} ## Typography {id="typography"}
import { H1, H2, H3, H4, H5, Label } from 'components/typography'
> #### Markdown > #### Markdown
> >
> ```markdown_ > ```markdown_
@ -147,8 +141,6 @@ Special link styles are used depending on the link URL.
### Abbreviations {id="abbr"} ### Abbreviations {id="abbr"}
import { Abbr } from 'components/typography'
> #### JSX > #### JSX
> >
> ```jsx > ```jsx
@ -161,8 +153,6 @@ abbreviation.
### Tags {id="tags"} ### Tags {id="tags"}
import Tag from 'components/tag'
> ```jsx > ```jsx
> <Tag>method</Tag> > <Tag>method</Tag>
> <Tag variant="version">4</Tag> > <Tag variant="version">4</Tag>
@ -186,8 +176,6 @@ installed.
### Buttons {id="buttons"} ### Buttons {id="buttons"}
import Button from 'components/button'
> ```jsx > ```jsx
> <Button to="#" variant="primary">Primary small</Button> > <Button to="#" variant="primary">Primary small</Button>
> <Button to="#" variant="secondary">Secondary small</Button> > <Button to="#" variant="secondary">Secondary small</Button>
@ -477,8 +465,6 @@ https://github.com/explosion/spaCy/tree/master/spacy/language.py
### Infobox {id="infobox"} ### Infobox {id="infobox"}
import Infobox from 'components/infobox'
> #### JSX > #### JSX
> >
> ```jsx > ```jsx
@ -515,8 +501,6 @@ blocks.
### Accordion {id="accordion"} ### Accordion {id="accordion"}
import Accordion from 'components/accordion'
> #### JSX > #### JSX
> >
> ```jsx > ```jsx

View File

@ -32,8 +32,6 @@ for ent in doc.ents:
Using spaCy's built-in [displaCy visualizer](/usage/visualizers), here's what Using spaCy's built-in [displaCy visualizer](/usage/visualizers), here's what
our example sentence and its named entities look like: our example sentence and its named entities look like:
import { Iframe } from 'components/embed'
<Iframe <Iframe
title="displaCy visualization of entities" title="displaCy visualization of entities"
src="/images/displacy-ent1.html" src="/images/displacy-ent1.html"

View File

@ -35,8 +35,6 @@ the [config](/usage/training#config):
pipeline = ["tok2vec", "tagger", "parser", "ner"] pipeline = ["tok2vec", "tagger", "parser", "ner"]
``` ```
import Accordion from 'components/accordion.js'
<Accordion title="Does the order of pipeline components matter?" id="pipeline-components-order"> <Accordion title="Does the order of pipeline components matter?" id="pipeline-components-order">
The statistical components like the tagger or parser are typically independent The statistical components like the tagger or parser are typically independent

View File

@ -57,8 +57,6 @@ for token in doc:
Using spaCy's built-in [displaCy visualizer](/usage/visualizers), here's what Using spaCy's built-in [displaCy visualizer](/usage/visualizers), here's what
our example sentence and its dependencies look like: our example sentence and its dependencies look like:
import { Iframe } from 'components/embed'
<Iframe <Iframe
title="displaCy visualization of dependencies and entities" title="displaCy visualization of dependencies and entities"
src="/images/displacy-long.html" src="/images/displacy-long.html"

View File

@ -1,5 +1,3 @@
import Infobox from 'components/infobox'
Similarity is determined by comparing **word vectors** or "word embeddings", Similarity is determined by comparing **word vectors** or "word embeddings",
multi-dimensional meaning representations of a word. Word vectors can be multi-dimensional meaning representations of a word. Word vectors can be
generated using an algorithm like generated using an algorithm like

View File

@ -1,6 +1,3 @@
import { Help } from 'components/typography'
import Link from 'components/link'
<figure> <figure>
| Pipeline | Parser | Tagger | NER | | Pipeline | Parser | Tagger | NER |

View File

@ -18,8 +18,6 @@ understanding systems.
### Feature overview {id="comparison-features"} ### Feature overview {id="comparison-features"}
import Features from 'widgets/features.js'
<Features /> <Features />
### When should I use spaCy? {id="comparison-usage"} ### When should I use spaCy? {id="comparison-usage"}
@ -69,8 +67,6 @@ pipeline, which is less accurate but much cheaper to run.
> gold-standard segmentation and tokenization, from a pretty specific type of > gold-standard segmentation and tokenization, from a pretty specific type of
> text (articles from a single newspaper, 1984-1989). > text (articles from a single newspaper, 1984-1989).
import Benchmarks from 'usage/_benchmarks-models.mdx'
<Benchmarks /> <Benchmarks />
<figure> <figure>

View File

@ -16,8 +16,6 @@ menu:
> website to [**v2.spacy.io**](https://v2.spacy.io/docs). To see what's changed > website to [**v2.spacy.io**](https://v2.spacy.io/docs). To see what's changed
> and how to migrate, see the [v3.0 guide](/usage/v3). > and how to migrate, see the [v3.0 guide](/usage/v3).
import QuickstartInstall from 'widgets/quickstart-install.js'
<QuickstartInstall id="quickstart" /> <QuickstartInstall id="quickstart" />
## Installation instructions {id="installation"} ## Installation instructions {id="installation"}
@ -449,6 +447,4 @@ either of these, clone your repository again.
## Changelog {id="changelog"} ## Changelog {id="changelog"}
import Changelog from 'widgets/changelog.js'
<Changelog /> <Changelog />

View File

@ -28,8 +28,6 @@ annotations.
## Part-of-speech tagging {id="pos-tagging",model="tagger, parser"} ## Part-of-speech tagging {id="pos-tagging",model="tagger, parser"}
import PosDeps101 from 'usage/101/_pos-deps.mdx'
<PosDeps101 /> <PosDeps101 />
<Infobox title="Part-of-speech tag scheme" emoji="📖"> <Infobox title="Part-of-speech tag scheme" emoji="📖">
@ -538,8 +536,6 @@ with new examples.
### Named Entity Recognition 101 {id="named-entities-101"} ### Named Entity Recognition 101 {id="named-entities-101"}
import NER101 from 'usage/101/_named-entities.mdx'
<NER101 /> <NER101 />
### Accessing entity annotations and labels {id="accessing-ner"} ### Accessing entity annotations and labels {id="accessing-ner"}
@ -789,8 +785,6 @@ during tokenization. This is kind of a core principle of spaCy's `Doc` object:
</Infobox> </Infobox>
import Tokenization101 from 'usage/101/_tokenization.mdx'
<Tokenization101 /> <Tokenization101 />
<Accordion title="Algorithm details: How spaCy's tokenizer works" id="how-tokenizer-works" spaced> <Accordion title="Algorithm details: How spaCy's tokenizer works" id="how-tokenizer-works" spaced>
@ -1872,8 +1866,6 @@ initialized before training. See the
## Word vectors and semantic similarity {id="vectors-similarity"} ## Word vectors and semantic similarity {id="vectors-similarity"}
import Vectors101 from 'usage/101/_vectors-similarity.mdx'
<Vectors101 /> <Vectors101 />
### Adding word vectors {id="adding-vectors"} ### Adding word vectors {id="adding-vectors"}
@ -2002,8 +1994,6 @@ for word, vector in vector_data.items():
## Language Data {id="language-data"} ## Language Data {id="language-data"}
import LanguageData101 from 'usage/101/_language-data.mdx'
<LanguageData101 /> <LanguageData101 />
### Creating a custom language subclass {id="language-subclass"} ### Creating a custom language subclass {id="language-subclass"}

View File

@ -23,8 +23,6 @@ located anywhere on your file system.
## Quickstart {hidden="true"} ## Quickstart {hidden="true"}
import QuickstartModels from 'widgets/quickstart-models.js'
<QuickstartModels <QuickstartModels
title="Quickstart" title="Quickstart"
id="quickstart" id="quickstart"
@ -70,8 +68,6 @@ contribute to development. Also see the
[training documentation](/usage/training) for how to train your own pipelines on [training documentation](/usage/training) for how to train your own pipelines on
your data. your data.
import Languages from 'widgets/languages.js'
<Languages /> <Languages />
### Multi-language support {id="multi-language",version="2"} ### Multi-language support {id="multi-language",version="2"}

View File

@ -12,8 +12,6 @@ menu:
- ['Plugins & Wrappers', 'plugins'] - ['Plugins & Wrappers', 'plugins']
--- ---
import Pipelines101 from 'usage/101/_pipelines.mdx'
<Pipelines101 /> <Pipelines101 />
## Processing text {id="processing"} ## Processing text {id="processing"}

View File

@ -10,8 +10,6 @@ menu:
## Basics {id="basics",hidden="true"} ## Basics {id="basics",hidden="true"}
import Serialization101 from 'usage/101/_serialization.mdx'
<Serialization101 /> <Serialization101 />
### Serializing the pipeline {id="pipeline"} ### Serializing the pipeline {id="pipeline"}

View File

@ -195,8 +195,6 @@ text with spaCy.
### Tokenization {id="annotations-token"} ### Tokenization {id="annotations-token"}
import Tokenization101 from 'usage/101/_tokenization.mdx'
<Tokenization101 /> <Tokenization101 />
<Infobox title="Tokenization rules" emoji="📖"> <Infobox title="Tokenization rules" emoji="📖">
@ -211,8 +209,6 @@ language-specific data**, see the usage guides on
### Part-of-speech tags and dependencies {id="annotations-pos-deps",model="parser"} ### Part-of-speech tags and dependencies {id="annotations-pos-deps",model="parser"}
import PosDeps101 from 'usage/101/_pos-deps.mdx'
<PosDeps101 /> <PosDeps101 />
<Infobox title="Part-of-speech tagging and morphology" emoji="📖"> <Infobox title="Part-of-speech tagging and morphology" emoji="📖">
@ -226,8 +222,6 @@ how to **navigate and use the parse tree** effectively, see the usage guides on
### Named Entities {id="annotations-ner",model="ner"} ### Named Entities {id="annotations-ner",model="ner"}
import NER101 from 'usage/101/_named-entities.mdx'
<NER101 /> <NER101 />
<Infobox title="Named Entity Recognition" emoji="📖"> <Infobox title="Named Entity Recognition" emoji="📖">
@ -242,8 +236,6 @@ of a model, see the usage guides on
### Word vectors and similarity {id="vectors-similarity",model="vectors"} ### Word vectors and similarity {id="vectors-similarity",model="vectors"}
import Vectors101 from 'usage/101/_vectors-similarity.mdx'
<Vectors101 /> <Vectors101 />
<Infobox title="Word vectors" emoji="📖"> <Infobox title="Word vectors" emoji="📖">
@ -256,8 +248,6 @@ To learn more about word vectors, how to **customize them** and how to load
## Pipelines {id="pipelines"} ## Pipelines {id="pipelines"}
import Pipelines101 from 'usage/101/_pipelines.mdx'
<Pipelines101 /> <Pipelines101 />
<Infobox title="Processing pipelines" emoji="📖"> <Infobox title="Processing pipelines" emoji="📖">
@ -270,8 +260,6 @@ guide on [language processing pipelines](/usage/processing-pipelines).
## Architecture {id="architecture"} ## Architecture {id="architecture"}
import Architecture101 from 'usage/101/_architecture.mdx'
<Architecture101 /> <Architecture101 />
## Vocab, hashes and lexemes {id="vocab"} ## Vocab, hashes and lexemes {id="vocab"}
@ -388,8 +376,6 @@ it.
## Serialization {id="serialization"} ## Serialization {id="serialization"}
import Serialization101 from 'usage/101/_serialization.mdx'
<Serialization101 /> <Serialization101 />
<Infobox title="Saving and loading" emoji="📖"> <Infobox title="Saving and loading" emoji="📖">
@ -401,8 +387,6 @@ guide on [saving and loading](/usage/saving-loading#models).
## Training {id="training"} ## Training {id="training"}
import Training101 from 'usage/101/_training.mdx'
<Training101 /> <Training101 />
<Infobox title="Training pipelines and models" emoji="📖"> <Infobox title="Training pipelines and models" emoji="📖">
@ -480,8 +464,6 @@ for trainable components.
## Language data {id="language-data"} ## Language data {id="language-data"}
import LanguageData101 from 'usage/101/_language-data.mdx'
<LanguageData101 /> <LanguageData101 />
## Community & FAQ {id="community-faq"} ## Community & FAQ {id="community-faq"}

View File

@ -17,8 +17,6 @@ menu:
## Introduction to training {id="basics",hidden="true"} ## Introduction to training {id="basics",hidden="true"}
import Training101 from 'usage/101/_training.mdx'
<Training101 /> <Training101 />
<Infobox title="Tip: Try the Prodigy annotation tool"> <Infobox title="Tip: Try the Prodigy annotation tool">
@ -69,8 +67,6 @@ config.
> requirements and settings as CLI arguments. > requirements and settings as CLI arguments.
> 2. Run [`train`](/api/cli#train) with the exported config and data. > 2. Run [`train`](/api/cli#train) with the exported config and data.
import QuickstartTraining from 'widgets/quickstart-training.js'
<QuickstartTraining /> <QuickstartTraining />
After you've saved the starter config to a file `base_config.cfg`, you can use After you've saved the starter config to a file `base_config.cfg`, you can use

View File

@ -88,8 +88,6 @@ giving you access to thousands of pretrained models for your pipelines.
![Pipeline components listening to shared embedding component](/images/tok2vec-listener.svg) ![Pipeline components listening to shared embedding component](/images/tok2vec-listener.svg)
import Benchmarks from 'usage/_benchmarks-models.mdx'
<Benchmarks /> <Benchmarks />
#### New trained transformer-based pipelines {id="features-transformers-pipelines"} #### New trained transformer-based pipelines {id="features-transformers-pipelines"}