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Add spaCy Tailored Pipelines
This commit is contained in:
Ines Montani
parent
42072f4468
commit
f2c2b97e56
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@ -33,7 +33,7 @@ open-source software, released under the MIT license.
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## 📖 Documentation
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## 📖 Documentation
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| Documentation | |
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| Documentation | |
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| -------------------------- | -------------------------------------------------------------- |
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| ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| ⭐️ **[spaCy 101]** | New to spaCy? Here's everything you need to know! |
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| ⭐️ **[spaCy 101]** | New to spaCy? Here's everything you need to know! |
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| 📚 **[Usage Guides]** | How to use spaCy and its features. |
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| 📚 **[Usage Guides]** | How to use spaCy and its features. |
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| 🚀 **[New in v3.0]** | New features, backwards incompatibilities and migration guide. |
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| 🚀 **[New in v3.0]** | New features, backwards incompatibilities and migration guide. |
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@ -45,6 +45,7 @@ open-source software, released under the MIT license.
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| 📺 **[Videos]** | Our YouTube channel with video tutorials, talks and more. |
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| 📺 **[Videos]** | Our YouTube channel with video tutorials, talks and more. |
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| 🛠 **[Changelog]** | Changes and version history. |
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| 🛠 **[Changelog]** | Changes and version history. |
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| 💝 **[Contribute]** | How to contribute to the spaCy project and code base. |
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| 💝 **[Contribute]** | How to contribute to the spaCy project and code base. |
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| <a href="https://explosion.ai/spacy-tailored-pipelines"><img src="https://user-images.githubusercontent.com/13643239/152853098-1c761611-ccb0-4ec6-9066-b234552831fe.png" width="125" alt="spaCy Tailored Pipelines"/></a> | Get a custom spaCy pipeline, tailor-made for your NLP problem by spaCy's core developers. Streamlined, production-ready, predictable and maintainable. Start by completing our 5-minute questionnaire to tell us what you need and we'll be in touch! **[Learn more →](https://explosion.ai/spacy-tailored-pipelines)** |
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[spacy 101]: https://spacy.io/usage/spacy-101
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[spacy 101]: https://spacy.io/usage/spacy-101
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[new in v3.0]: https://spacy.io/usage/v3
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[new in v3.0]: https://spacy.io/usage/v3
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@ -60,9 +61,7 @@ open-source software, released under the MIT license.
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## 💬 Where to ask questions
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## 💬 Where to ask questions
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The spaCy project is maintained by **[@honnibal](https://github.com/honnibal)**,
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The spaCy project is maintained by the [spaCy team](https://explosion.ai/about).
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**[@ines](https://github.com/ines)**, **[@svlandeg](https://github.com/svlandeg)**,
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**[@adrianeboyd](https://github.com/adrianeboyd)** and **[@polm](https://github.com/polm)**.
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Please understand that we won't be able to provide individual support via email.
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Please understand that we won't be able to provide individual support via email.
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We also believe that help is much more valuable if it's shared publicly, so that
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We also believe that help is much more valuable if it's shared publicly, so that
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more people can benefit from it.
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more people can benefit from it.
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BIN
website/docs/images/spacy-tailored-pipelines_wide.png
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BIN
website/docs/images/spacy-tailored-pipelines_wide.png
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Binary file not shown.
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After Width: | Height: | Size: 44 KiB |
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@ -40,7 +40,11 @@
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"label": "Resources",
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"label": "Resources",
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"items": [
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"items": [
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{ "text": "Project Templates", "url": "https://github.com/explosion/projects" },
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{ "text": "Project Templates", "url": "https://github.com/explosion/projects" },
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{ "text": "v2.x Documentation", "url": "https://v2.spacy.io" }
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{ "text": "v2.x Documentation", "url": "https://v2.spacy.io" },
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{
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"text": "Custom Solutions",
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"url": "https://explosion.ai/spacy-tailored-pipelines"
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}
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]
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]
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}
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}
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]
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]
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@ -48,7 +48,11 @@
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{ "text": "Usage", "url": "/usage" },
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{ "text": "Usage", "url": "/usage" },
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{ "text": "Models", "url": "/models" },
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{ "text": "Models", "url": "/models" },
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{ "text": "API Reference", "url": "/api" },
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{ "text": "API Reference", "url": "/api" },
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{ "text": "Online Course", "url": "https://course.spacy.io" }
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{ "text": "Online Course", "url": "https://course.spacy.io" },
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{
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"text": "Custom Solutions",
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"url": "https://explosion.ai/spacy-tailored-pipelines"
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}
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]
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]
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},
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},
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{
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{
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@ -6,11 +6,14 @@ import { replaceEmoji } from './icon'
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export const Ol = props => <ol className={classes.ol} {...props} />
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export const Ol = props => <ol className={classes.ol} {...props} />
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export const Ul = props => <ul className={classes.ul} {...props} />
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export const Ul = props => <ul className={classes.ul} {...props} />
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export const Li = ({ children, ...props }) => {
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export const Li = ({ children, emoji, ...props }) => {
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const { hasIcon, content } = replaceEmoji(children)
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const { hasIcon, content } = replaceEmoji(children)
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const liClassNames = classNames(classes.li, { [classes.liIcon]: hasIcon })
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const liClassNames = classNames(classes.li, {
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[classes.liIcon]: hasIcon,
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[classes.emoji]: emoji,
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})
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return (
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return (
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<li className={liClassNames} {...props}>
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<li data-emoji={emoji} className={liClassNames} {...props}>
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{content}
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{content}
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</li>
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</li>
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)
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)
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@ -36,6 +36,16 @@
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box-sizing: content-box
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box-sizing: content-box
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vertical-align: top
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vertical-align: top
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.emoji:before
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content: attr(data-emoji)
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padding-right: 0.75em
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padding-top: 0
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margin-left: -2.5em
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width: 1.75em
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text-align: right
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font-size: 1em
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position: static
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.li-icon
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.li-icon
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text-indent: calc(-20px - 0.55em)
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text-indent: calc(-20px - 0.55em)
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@ -15,9 +15,9 @@ import {
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} from '../components/landing'
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} from '../components/landing'
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import { H2 } from '../components/typography'
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import { H2 } from '../components/typography'
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import { InlineCode } from '../components/code'
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import { InlineCode } from '../components/code'
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import { Ul, Li } from '../components/list'
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import Button from '../components/button'
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import Button from '../components/button'
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import Link from '../components/link'
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import Link from '../components/link'
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import { YouTube } from '../components/embed'
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import QuickstartTraining from './quickstart-training'
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import QuickstartTraining from './quickstart-training'
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import Project from './project'
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import Project from './project'
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@ -25,6 +25,7 @@ import Features from './features'
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import courseImage from '../../docs/images/course.jpg'
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import courseImage from '../../docs/images/course.jpg'
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import prodigyImage from '../../docs/images/prodigy_overview.jpg'
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import prodigyImage from '../../docs/images/prodigy_overview.jpg'
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import projectsImage from '../../docs/images/projects.png'
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import projectsImage from '../../docs/images/projects.png'
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import tailoredPipelinesImage from '../../docs/images/spacy-tailored-pipelines_wide.png'
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import Benchmarks from 'usage/_benchmarks-models.md'
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import Benchmarks from 'usage/_benchmarks-models.md'
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@ -104,23 +105,45 @@ const Landing = ({ data }) => {
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<LandingBannerGrid>
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<LandingBannerGrid>
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<LandingBanner
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<LandingBanner
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label="New in v3.0"
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to="https://explosion.ai/spacy-tailored-pipelines"
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title="Transformer-based pipelines, new training system, project templates & more"
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button="Learn more"
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to="/usage/v3"
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background="#E4F4F9"
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button="See what's new"
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color="#1e1935"
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small
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small
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>
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>
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spaCy v3.0 features all new <strong>transformer-based pipelines</strong> that
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<Link to="https://explosion.ai/spacy-tailored-pipelines" hidden>
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bring spaCy's accuracy right up to the current <strong>state-of-the-art</strong>
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<img src={tailoredPipelinesImage} alt="spaCy Tailored Pipelines" />
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. You can use any pretrained transformer to train your own pipelines, and even
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</Link>
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share one transformer between multiple components with{' '}
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<strong>
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<strong>multi-task learning</strong>. Training is now fully configurable and
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Get a custom spaCy pipeline, tailor-made for your NLP problem by spaCy's
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extensible, and you can define your own custom models using{' '}
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core developers.
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<strong>PyTorch</strong>, <strong>TensorFlow</strong> and other frameworks. The
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</strong>
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new spaCy projects system lets you describe whole{' '}
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<br />
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<strong>end-to-end workflows</strong> in a single file, giving you an easy path
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<br />
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from prototype to production, and making it easy to clone and adapt
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<Ul>
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best-practice projects for your own use cases.
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<Li emoji="🔥">
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<strong>Streamlined.</strong> Nobody knows spaCy better than we do. Send
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us your pipeline requirements and we'll be ready to start producing your
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solution in no time at all.
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</Li>
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<Li emoji="🐿 ">
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<strong>Production ready.</strong> spaCy pipelines are robust and easy
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to deploy. You'll get a complete spaCy project folder which is ready to{' '}
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<InlineCode>spacy project run</InlineCode>.
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</Li>
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<Li emoji="🔮">
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<strong>Predictable.</strong> You'll know exactly what you're going to
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get and what it's going to cost. We quote fees up-front, let you try
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before you buy, and don't charge for over-runs at our end — all the risk
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is on us.
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</Li>
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<Li emoji="🛠">
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<strong>Maintainable.</strong> spaCy is an industry standard, and we'll
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deliver your pipeline with full code, data, tests and documentation, so
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your team can retrain, update and extend the solution as your
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requirements change.
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</Li>
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</Ul>
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</LandingBanner>
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</LandingBanner>
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<LandingBanner
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<LandingBanner
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@ -206,8 +229,20 @@ const Landing = ({ data }) => {
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</LandingGrid>
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</LandingGrid>
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<LandingBannerGrid>
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<LandingBannerGrid>
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<LandingBanner background="#0099dd" color="#ffffff" small>
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<LandingBanner
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<YouTube id="9k_EfV7Cns0" />
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label="New in v3.0"
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title="Transformer-based pipelines, new training system, project templates & more"
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to="/usage/v3"
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button="See what's new"
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small
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>
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spaCy v3.0 features all new <strong>transformer-based pipelines</strong> that
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bring spaCy's accuracy right up to the current <strong>state-of-the-art</strong>
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. You can use any pretrained transformer to train your own pipelines, and even
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share one transformer between multiple components with{' '}
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<strong>multi-task learning</strong>. Training is now fully configurable and
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extensible, and you can define your own custom models using{' '}
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<strong>PyTorch</strong>, <strong>TensorFlow</strong> and other frameworks.
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</LandingBanner>
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</LandingBanner>
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<LandingBanner
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<LandingBanner
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to="https://course.spacy.io"
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to="https://course.spacy.io"
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