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Marcus Blättermann
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@ -2,93 +2,103 @@
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# spaCy Universe
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The [spaCy Universe](https://spacy.io/universe) collects the many great resources developed with or for spaCy. It
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includes standalone packages, plugins, extensions, educational materials,
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operational utilities and bindings for other languages.
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The [spaCy Universe](https://spacy.io/universe) collects the many great
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resources developed with or for spaCy. It includes standalone packages, plugins,
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extensions, educational materials, operational utilities and bindings for other
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languages.
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If you have a project that you want the spaCy community to make use of, you can
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suggest it by submitting a pull request to this repository. The Universe
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database is open-source and collected in a simple JSON file.
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Looking for inspiration for your own spaCy plugin or extension? Check out the
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[`project ideas`](https://github.com/explosion/spaCy/discussions?discussions_q=category%3A%22New+Features+%26+Project+Ideas%22)
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[`project ideas`](https://github.com/explosion/spaCy/discussions?discussions_q=category%3A%22New+Features+%26+Project+Ideas%22)
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discussion forum.
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## Checklist
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### Projects
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✅ Libraries and packages should be **open-source** (with a user-friendly license) and at least somewhat **documented** (e.g. a simple `README` with usage instructions).
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✅ Libraries and packages should be **open-source** (with a user-friendly
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license) and at least somewhat **documented** (e.g. a simple `README` with usage
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instructions).
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✅ We're happy to include work in progress and prereleases, but we'd like to keep the emphasis on projects that should be useful to the community **right away**.
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✅ We're happy to include work in progress and prereleases, but we'd like to
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keep the emphasis on projects that should be useful to the community **right
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away**.
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✅ Demos and visualizers should be available via a **public URL**.
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### Educational Materials
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✅ Books should be **available for purchase or download** (not just pre-order). Ebooks and self-published books are fine, too, if they include enough substantial content.
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✅ Books should be **available for purchase or download** (not just pre-order).
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Ebooks and self-published books are fine, too, if they include enough
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substantial content.
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✅ The `"url"` of book entries should either point to the publisher's website or a reseller of your choice (ideally one that ships worldwide or as close as possible).
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✅ The `"url"` of book entries should either point to the publisher's website or
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a reseller of your choice (ideally one that ships worldwide or as close as
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possible).
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✅ If an online course is only available behind a paywall, it should at least have a **free excerpt** or chapter available, so users know what to expect.
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✅ If an online course is only available behind a paywall, it should at least
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have a **free excerpt** or chapter available, so users know what to expect.
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## JSON format
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To add a project, fork this repository, edit the [`universe.json`](meta/universe.json)
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and add an object of the following format to the list of `"resources"`. Before
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you submit your pull request, make sure to use a linter to verify that your
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markup is correct.
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To add a project, fork this repository, edit the
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[`universe.json`](meta/universe.json) and add an object of the following format
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to the list of `"resources"`. Before you submit your pull request, make sure to
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use a linter to verify that your markup is correct.
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```json
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{
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"id": "unique-project-id",
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"title": "Project title",
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"slogan": "A short summary",
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"description": "A longer description – *Markdown allowed!*",
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"github": "user/repo",
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"pip": "package-name",
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"code_example": [
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"import spacy",
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"import package_name",
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"",
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"nlp = spacy.load('en')",
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"nlp.add_pipe(package_name)"
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],
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"code_language": "python",
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"url": "https://example.com",
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"thumb": "https://example.com/thumb.jpg",
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"image": "https://example.com/image.jpg",
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"author": "Your Name",
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"author_links": {
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"twitter": "username",
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"github": "username",
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"website": "https://example.com"
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},
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"category": ["pipeline", "standalone"],
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"tags": ["some-tag", "etc"]
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"id": "unique-project-id",
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"title": "Project title",
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"slogan": "A short summary",
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"description": "A longer description – *Markdown allowed!*",
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"github": "user/repo",
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"pip": "package-name",
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"code_example": [
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"import spacy",
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"import package_name",
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"",
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"nlp = spacy.load('en')",
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"nlp.add_pipe(package_name)"
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],
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"code_language": "python",
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"url": "https://example.com",
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"thumb": "https://example.com/thumb.jpg",
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"image": "https://example.com/image.jpg",
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"author": "Your Name",
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"author_links": {
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"twitter": "username",
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"github": "username",
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"website": "https://example.com"
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},
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"category": ["pipeline", "standalone"],
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"tags": ["some-tag", "etc"]
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}
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```
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| Field | Type | Description |
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| --- | --- | --- |
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| `id` | string | Unique ID of the project. |
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| `title` | string | Project title. If not set, the `id` will be used as the display title. |
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| `slogan` | string | A short description of the project. Displayed in the overview and under the title. |
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| `description` | string | A longer description of the project. Markdown is allowed, but should be limited to basic formatting like bold, italics, code or links. |
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| `github` | string | Associated GitHub repo in the format `user/repo`. Will be displayed as a link and used for release, license and star badges. |
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| `pip` | string | Package name on pip. If available, the installation command will be displayed. |
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| `cran` | string | For R packages: package name on CRAN. If available, the installation command will be displayed. |
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| `code_example` | array | Short example that shows how to use the project. Formatted as an array with one string per line. |
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| `code_language` | string | Defaults to `'python'`. Optional code language used for syntax highlighting with [Prism](http://prismjs.com/). |
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| `url` | string | Optional project link to display as button. |
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| `thumb` | string | Optional URL to project thumbnail to display in overview and project header. Recommended size is 100x100px. |
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| `image` | string | Optional URL to project image to display with description. |
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| `author` | string | Name(s) of project author(s). |
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| `author_links` | object | Usernames and links to display as icons to author info. Currently supports `twitter` and `github` usernames, as well as `website` link. |
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| `category` | list | One or more categories to assign to project. Must be one of the available options. |
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| `tags` | list | Still experimental and not used for filtering: one or more tags to assign to project. |
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| Field | Type | Description |
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| --------------- | ------ | --------------------------------------------------------------------------------------------------------------------------------------- |
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| `id` | string | Unique ID of the project. |
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| `title` | string | Project title. If not set, the `id` will be used as the display title. |
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| `slogan` | string | A short description of the project. Displayed in the overview and under the title. |
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| `description` | string | A longer description of the project. Markdown is allowed, but should be limited to basic formatting like bold, italics, code or links. |
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| `github` | string | Associated GitHub repo in the format `user/repo`. Will be displayed as a link and used for release, license and star badges. |
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| `pip` | string | Package name on pip. If available, the installation command will be displayed. |
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| `cran` | string | For R packages: package name on CRAN. If available, the installation command will be displayed. |
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| `code_example` | array | Short example that shows how to use the project. Formatted as an array with one string per line. |
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| `code_language` | string | Defaults to `'python'`. Optional code language used for syntax highlighting with [Prism](http://prismjs.com/). |
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| `url` | string | Optional project link to display as button. |
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| `thumb` | string | Optional URL to project thumbnail to display in overview and project header. Recommended size is 100x100px. |
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| `image` | string | Optional URL to project image to display with description. |
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| `author` | string | Name(s) of project author(s). |
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| `author_links` | object | Usernames and links to display as icons to author info. Currently supports `twitter` and `github` usernames, as well as `website` link. |
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| `category` | list | One or more categories to assign to project. Must be one of the available options. |
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| `tags` | list | Still experimental and not used for filtering: one or more tags to assign to project. |
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To separate them from the projects, educational materials also specify
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`"type": "education`. Books can also set a `"cover"` field containing a URL
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to a cover image. If available, it's used in the overview and displayed on
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the individual book page.
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`"type": "education`. Books can also set a `"cover"` field containing a URL to a
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cover image. If available, it's used in the overview and displayed on the
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individual book page.
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|
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@ -390,7 +390,7 @@ in other components, see
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| | |
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<Infobox title="Mixed precision support" variant="warning">
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Mixed-precision support is currently an experimental feature.
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Mixed-precision support is currently an experimental feature.
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</Infobox>
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<Accordion title="Previous versions of spacy-transformers.TransformerModel" spaced>
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@ -467,7 +467,7 @@ one component.
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| **CREATES** | The model using the architecture. ~~Model[List[Doc], List[Floats2d]]~~ |
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<Infobox title="Mixed precision support" variant="warning">
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Mixed-precision support is currently an experimental feature.
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Mixed-precision support is currently an experimental feature.
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</Infobox>
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<Accordion title="Previous versions of spacy-transformers.Tok2VecTransformer" spaced>
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@ -41,10 +41,9 @@ from string attribute names to internal attribute IDs is stored in
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The corresponding [`Token` object attributes](/api/token#attributes) can be
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accessed using the same names in lowercase, e.g. `token.orth` or `token.length`.
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For attributes that represent string values, the internal integer ID is
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accessed as `Token.attr`, e.g. `token.dep`, while the string value can be
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retrieved by appending `_` as in `token.dep_`.
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For attributes that represent string values, the internal integer ID is accessed
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as `Token.attr`, e.g. `token.dep`, while the string value can be retrieved by
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appending `_` as in `token.dep_`.
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| Attribute | Description |
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| ------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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|
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@ -474,7 +474,7 @@ report span characteristics such as the average span length and the span (or
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span boundary) distinctiveness. The distinctiveness measure shows how different
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the tokens are with respect to the rest of the corpus using the KL-divergence of
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the token distributions. To learn more, you can check out Papay et al.'s work on
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[*Dissecting Span Identification Tasks with Performance Prediction* (EMNLP 2020)](https://aclanthology.org/2020.emnlp-main.396/).
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[_Dissecting Span Identification Tasks with Performance Prediction_ (EMNLP 2020)](https://aclanthology.org/2020.emnlp-main.396/).
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</Infobox>
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@ -1187,7 +1187,6 @@ be provided.
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> $ python -m spacy find-threshold my_nlp data.spacy spancat threshold spans_sc_f
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> ```
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| Name | Description |
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| ----------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
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| `model` | Pipeline to evaluate. Can be a package or a path to a data directory. ~~str (positional)~~ |
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|
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@ -87,7 +87,6 @@ come directly from
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| `A <++ B` | `B` is a right parent of `A`, i.e. `A` is a child of `B` and `A.i < B.i` _(not in Semgrex)_. |
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| `A <-- B` | `B` is a left parent of `A`, i.e. `A` is a child of `B` and `A.i > B.i` _(not in Semgrex)_. |
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## DependencyMatcher.\_\_init\_\_ {#init tag="method"}
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Create a `DependencyMatcher`.
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|
|
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@ -99,9 +99,9 @@ be a token pattern (list) or a phrase pattern (string). For example:
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## EntityRuler.initialize {#initialize tag="method" new="3"}
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Initialize the component with data and used before training to load in rules
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from a [pattern file](/usage/rule-based-matching/#entityruler-files). This method
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is typically called by [`Language.initialize`](/api/language#initialize) and
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lets you customize arguments it receives via the
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from a [pattern file](/usage/rule-based-matching/#entityruler-files). This
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method is typically called by [`Language.initialize`](/api/language#initialize)
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and lets you customize arguments it receives via the
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[`[initialize.components]`](/api/data-formats#config-initialize) block in the
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config.
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@ -210,10 +210,10 @@ of dicts) or a phrase pattern (string). For more details, see the usage guide on
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| ---------- | ---------------------------------------------------------------- |
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| `patterns` | The patterns to add. ~~List[Dict[str, Union[str, List[dict]]]]~~ |
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## EntityRuler.remove {#remove tag="method" new="3.2.1"}
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Remove a pattern by its ID from the entity ruler. A `ValueError` is raised if the ID does not exist.
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Remove a pattern by its ID from the entity ruler. A `ValueError` is raised if
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the ID does not exist.
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> #### Example
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>
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@ -224,9 +224,9 @@ Remove a pattern by its ID from the entity ruler. A `ValueError` is raised if th
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> ruler.remove("apple")
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> ```
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| Name | Description |
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| ---------- | ---------------------------------------------------------------- |
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| `id` | The ID of the pattern rule. ~~str~~ |
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| Name | Description |
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| ---- | ----------------------------------- |
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| `id` | The ID of the pattern rule. ~~str~~ |
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## EntityRuler.to_disk {#to_disk tag="method"}
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|
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@ -288,9 +288,9 @@ Calculate alignment tables between two tokenizations.
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### Alignment attributes {#alignment-attributes"}
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Alignment attributes are managed using `AlignmentArray`, which is a
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simplified version of Thinc's [Ragged](https://thinc.ai/docs/api-types#ragged)
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type that only supports the `data` and `length` attributes.
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Alignment attributes are managed using `AlignmentArray`, which is a simplified
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version of Thinc's [Ragged](https://thinc.ai/docs/api-types#ragged) type that
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only supports the `data` and `length` attributes.
|
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| Name | Description |
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| ----- | ------------------------------------------------------------------------------------- |
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|
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@ -3,6 +3,6 @@ title: Library Architecture
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next: /api/architectures
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---
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import Architecture101 from 'usage/101/\_architecture.mdx'
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import Architecture101 from 'usage/101/_architecture.mdx'
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<Architecture101 />
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|
|
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@ -106,7 +106,7 @@ to you.
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## KnowledgeBase.get_alias_candidates {#get_alias_candidates tag="method"}
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<Infobox variant="warning">
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This method is _not_ available from spaCy 3.5 onwards.
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This method is _not_ available from spaCy 3.5 onwards.
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</Infobox>
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From spaCy 3.5 on `KnowledgeBase` is an abstract class (with
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|
|
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@ -105,11 +105,11 @@ representation.
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## Attributes {#attributes}
|
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| Name | Description |
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| ------------- | ------------------------------------------------------------------------------------------------------------------------------ |
|
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| `FEATURE_SEP` | The [FEATS](https://universaldependencies.org/format.html#morphological-annotation) feature separator. Default is `|`. ~~str~~ |
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| `FIELD_SEP` | The [FEATS](https://universaldependencies.org/format.html#morphological-annotation) field separator. Default is `=`. ~~str~~ |
|
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| `VALUE_SEP` | The [FEATS](https://universaldependencies.org/format.html#morphological-annotation) value separator. Default is `,`. ~~str~~ |
|
||||
| Name | Description |
|
||||
| ------------- | ---------------------------------------------------------------------------------------------------------------------------- | ---------- |
|
||||
| `FEATURE_SEP` | The [FEATS](https://universaldependencies.org/format.html#morphological-annotation) feature separator. Default is ` | `. ~~str~~ |
|
||||
| `FIELD_SEP` | The [FEATS](https://universaldependencies.org/format.html#morphological-annotation) field separator. Default is `=`. ~~str~~ |
|
||||
| `VALUE_SEP` | The [FEATS](https://universaldependencies.org/format.html#morphological-annotation) value separator. Default is `,`. ~~str~~ |
|
||||
|
||||
## MorphAnalysis {#morphanalysis tag="class" source="spacy/tokens/morphanalysis.pyx"}
|
||||
|
||||
|
|
|
|||
|
|
@ -38,7 +38,7 @@ how the component should be configured. You can override its settings via the
|
|||
> ```
|
||||
|
||||
| Setting | Description |
|
||||
| ---------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------ |
|
||||
| ---------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------ | ------ |
|
||||
| `punct_chars` | Optional custom list of punctuation characters that mark sentence ends. See below for defaults if not set. Defaults to `None`. ~~Optional[List[str]]~~ | `None` |
|
||||
| `overwrite` <Tag variant="new">3.2</Tag> | Whether existing annotation is overwritten. Defaults to `False`. ~~bool~~ |
|
||||
| `scorer` <Tag variant="new">3.2</Tag> | The scoring method. Defaults to [`Scorer.score_spans`](/api/scorer#score_spans) for the attribute `"sents"` ~~Optional[Callable]~~ |
|
||||
|
|
|
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|
|
@ -1,58 +1,155 @@
|
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<svg xmlns="http://www.w3.org/2000/svg" xlink="http://www.w3.org/1999/xlink" xml:lang="en" id="c3124cc3e661444cb9d4175a5b7c09d1-0" class="displacy" width="925" height="399.5" direction="ltr" style="max-width: none; height: 399.5px; color: #000000; background: #ffffff; font-family: Arial; direction: ltr">
|
||||
<text class="displacy-token" fill="currentColor" text-anchor="middle" y="309.5">
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||||
<tspan class="displacy-word" fill="currentColor" x="50">Smith</tspan>
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||||
<tspan class="displacy-tag" dy="2em" fill="currentColor" x="50"></tspan>
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||||
</text>
|
||||
|
||||
<text class="displacy-token" fill="currentColor" text-anchor="middle" y="309.5">
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||||
<tspan class="displacy-word" fill="currentColor" x="225">founded</tspan>
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||||
<tspan class="displacy-tag" dy="2em" fill="currentColor" x="225"></tspan>
|
||||
</text>
|
||||
|
||||
<text class="displacy-token" fill="currentColor" text-anchor="middle" y="309.5">
|
||||
<tspan class="displacy-word" fill="currentColor" x="400">a</tspan>
|
||||
<tspan class="displacy-tag" dy="2em" fill="currentColor" x="400"></tspan>
|
||||
</text>
|
||||
|
||||
<text class="displacy-token" fill="currentColor" text-anchor="middle" y="309.5">
|
||||
<tspan class="displacy-word" fill="currentColor" x="575">healthcare</tspan>
|
||||
<tspan class="displacy-tag" dy="2em" fill="currentColor" x="575"></tspan>
|
||||
</text>
|
||||
|
||||
<text class="displacy-token" fill="currentColor" text-anchor="middle" y="309.5">
|
||||
<tspan class="displacy-word" fill="currentColor" x="750">company</tspan>
|
||||
<tspan class="displacy-tag" dy="2em" fill="currentColor" x="750"></tspan>
|
||||
</text>
|
||||
|
||||
<g class="displacy-arrow">
|
||||
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|
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style="
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padding: 0.45em 0.6em;
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margin: 0 0.25em;
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<span
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|
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style="
|
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font-size: 0.8em;
|
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font-weight: bold;
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line-height: 1;
|
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border-radius: 0.35em;
|
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text-transform: uppercase;
|
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vertical-align: middle;
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|
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style="
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background: linear-gradient(90deg, #aa9cfc, #fc9ce7);
|
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padding: 0.45em 0.6em;
|
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margin: 0 0.25em;
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line-height: 1;
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border-radius: 0.35em;
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|
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<span
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|
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style="
|
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font-size: 0.8em;
|
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font-weight: bold;
|
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line-height: 1;
|
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border-radius: 0.35em;
|
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text-transform: uppercase;
|
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vertical-align: middle;
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margin-left: 0.5rem;
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|
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|
|
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|
|
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🌱🌿
|
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____ 🌳🌲 ____
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style="
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<span
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style="
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line-height: 1;
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border-radius: 0.35em;
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vertical-align: middle;
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|
|
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|||
|
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@ -1,36 +1,83 @@
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<div
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class="entities"
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Apple
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|
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U.K.
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|
||||
>GPE</span
|
||||
>
|
||||
</mark>
|
||||
startup for
|
||||
<mark
|
||||
class="entity"
|
||||
style="background: #e4e7d2; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em"
|
||||
style="
|
||||
background: #e4e7d2;
|
||||
padding: 0.45em 0.6em;
|
||||
margin: 0 0.25em;
|
||||
line-height: 1;
|
||||
border-radius: 0.35em;
|
||||
"
|
||||
>
|
||||
$1 billion
|
||||
<span
|
||||
style="font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; text-transform: uppercase; vertical-align: middle; margin-left: 0.5rem"
|
||||
style="
|
||||
font-size: 0.8em;
|
||||
font-weight: bold;
|
||||
line-height: 1;
|
||||
border-radius: 0.35em;
|
||||
text-transform: uppercase;
|
||||
vertical-align: middle;
|
||||
margin-left: 0.5rem;
|
||||
"
|
||||
>MONEY</span
|
||||
>
|
||||
</mark>
|
||||
|
|
|
|||
|
|
@ -1,37 +1,84 @@
|
|||
<div
|
||||
class="entities"
|
||||
style="line-height: 2.5; font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Helvetica, Arial, sans-serif, 'Apple Color Emoji', 'Segoe UI Emoji', 'Segoe UI Symbol'; font-size: 18px"
|
||||
style="
|
||||
line-height: 2.5;
|
||||
font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Helvetica, Arial, sans-serif,
|
||||
'Apple Color Emoji', 'Segoe UI Emoji', 'Segoe UI Symbol';
|
||||
font-size: 18px;
|
||||
"
|
||||
>
|
||||
When
|
||||
<mark
|
||||
class="entity"
|
||||
style="background: #aa9cfc; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em"
|
||||
style="
|
||||
background: #aa9cfc;
|
||||
padding: 0.45em 0.6em;
|
||||
margin: 0 0.25em;
|
||||
line-height: 1;
|
||||
border-radius: 0.35em;
|
||||
"
|
||||
>
|
||||
Sebastian Thrun
|
||||
<span
|
||||
style="font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; text-transform: uppercase; vertical-align: middle; margin-left: 0.5rem"
|
||||
style="
|
||||
font-size: 0.8em;
|
||||
font-weight: bold;
|
||||
line-height: 1;
|
||||
border-radius: 0.35em;
|
||||
text-transform: uppercase;
|
||||
vertical-align: middle;
|
||||
margin-left: 0.5rem;
|
||||
"
|
||||
>PERSON</span
|
||||
>
|
||||
</mark>
|
||||
started working on self-driving cars at
|
||||
<mark
|
||||
class="entity"
|
||||
style="background: #7aecec; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em"
|
||||
style="
|
||||
background: #7aecec;
|
||||
padding: 0.45em 0.6em;
|
||||
margin: 0 0.25em;
|
||||
line-height: 1;
|
||||
border-radius: 0.35em;
|
||||
"
|
||||
>
|
||||
Google
|
||||
<span
|
||||
style="font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; text-transform: uppercase; vertical-align: middle; margin-left: 0.5rem"
|
||||
style="
|
||||
font-size: 0.8em;
|
||||
font-weight: bold;
|
||||
line-height: 1;
|
||||
border-radius: 0.35em;
|
||||
text-transform: uppercase;
|
||||
vertical-align: middle;
|
||||
margin-left: 0.5rem;
|
||||
"
|
||||
>ORG</span
|
||||
>
|
||||
</mark>
|
||||
in
|
||||
<mark
|
||||
class="entity"
|
||||
style="background: #bfe1d9; padding: 0.45em 0.6em; margin: 0 0.25em; line-height: 1; border-radius: 0.35em"
|
||||
style="
|
||||
background: #bfe1d9;
|
||||
padding: 0.45em 0.6em;
|
||||
margin: 0 0.25em;
|
||||
line-height: 1;
|
||||
border-radius: 0.35em;
|
||||
"
|
||||
>
|
||||
2007
|
||||
<span
|
||||
style="font-size: 0.8em; font-weight: bold; line-height: 1; border-radius: 0.35em; text-transform: uppercase; vertical-align: middle; margin-left: 0.5rem"
|
||||
style="
|
||||
font-size: 0.8em;
|
||||
font-weight: bold;
|
||||
line-height: 1;
|
||||
border-radius: 0.35em;
|
||||
text-transform: uppercase;
|
||||
vertical-align: middle;
|
||||
margin-left: 0.5rem;
|
||||
"
|
||||
>DATE</span
|
||||
>
|
||||
</mark>
|
||||
|
|
|
|||
|
|
@ -5,7 +5,13 @@
|
|||
class="displacy"
|
||||
width="1975"
|
||||
height="399.5"
|
||||
style="max-width: none; height: 399.5px; color: #000000; background: #ffffff; font-family: Arial"
|
||||
style="
|
||||
max-width: none;
|
||||
height: 399.5px;
|
||||
color: #000000;
|
||||
background: #ffffff;
|
||||
font-family: Arial;
|
||||
"
|
||||
>
|
||||
<text class="displacy-token" fill="currentColor" text-anchor="middle" y="309.5">
|
||||
<tspan class="displacy-word" fill="currentColor" x="50">Apple</tspan>
|
||||
|
|
|
|||
|
Before Width: | Height: | Size: 11 KiB After Width: | Height: | Size: 11 KiB |
|
|
@ -1,84 +1,212 @@
|
|||
<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" id="0" class="displacy" width="1275" height="399.5" style="max-width: none; height: 399.5px; color: #000000; background: #ffffff; font-family: Arial">
|
||||
<text class="displacy-token" fill="currentColor" text-anchor="middle" y="309.5">
|
||||
<tspan class="displacy-word" fill="currentColor" x="50">Autonomous</tspan>
|
||||
<tspan class="displacy-tag" dy="2em" fill="currentColor" x="50">ADJ</tspan>
|
||||
</text>
|
||||
|
||||
<text class="displacy-token" fill="currentColor" text-anchor="middle" y="309.5">
|
||||
<tspan class="displacy-word" fill="currentColor" x="225">cars</tspan>
|
||||
<tspan class="displacy-tag" dy="2em" fill="currentColor" x="225">NOUN</tspan>
|
||||
</text>
|
||||
|
||||
<text class="displacy-token" fill="currentColor" text-anchor="middle" y="309.5">
|
||||
<tspan class="displacy-word" fill="currentColor" x="400">shift</tspan>
|
||||
<tspan class="displacy-tag" dy="2em" fill="currentColor" x="400">VERB</tspan>
|
||||
</text>
|
||||
|
||||
<text class="displacy-token" fill="currentColor" text-anchor="middle" y="309.5">
|
||||
<tspan class="displacy-word" fill="currentColor" x="575">insurance</tspan>
|
||||
<tspan class="displacy-tag" dy="2em" fill="currentColor" x="575">NOUN</tspan>
|
||||
</text>
|
||||
|
||||
<text class="displacy-token" fill="currentColor" text-anchor="middle" y="309.5">
|
||||
<tspan class="displacy-word" fill="currentColor" x="750">liability</tspan>
|
||||
<tspan class="displacy-tag" dy="2em" fill="currentColor" x="750">NOUN</tspan>
|
||||
</text>
|
||||
|
||||
<text class="displacy-token" fill="currentColor" text-anchor="middle" y="309.5">
|
||||
<tspan class="displacy-word" fill="currentColor" x="925">toward</tspan>
|
||||
<tspan class="displacy-tag" dy="2em" fill="currentColor" x="925">ADP</tspan>
|
||||
</text>
|
||||
|
||||
<text class="displacy-token" fill="currentColor" text-anchor="middle" y="309.5">
|
||||
<tspan class="displacy-word" fill="currentColor" x="1100">manufacturers</tspan>
|
||||
<tspan class="displacy-tag" dy="2em" fill="currentColor" x="1100">NOUN</tspan>
|
||||
</text>
|
||||
|
||||
<g class="displacy-arrow">
|
||||
<path class="displacy-arc" id="arrow-0-0" stroke-width="2px" d="M70,264.5 C70,177.0 215.0,177.0 215.0,264.5" fill="none" stroke="currentColor"></path>
|
||||
<text dy="1.25em" style="font-size: 0.8em; letter-spacing: 1px">
|
||||
<textpath xlink:href="#arrow-0-0" class="displacy-label" startOffset="50%" fill="currentColor" text-anchor="middle">amod</textpath>
|
||||
<svg
|
||||
xmlns="http://www.w3.org/2000/svg"
|
||||
xmlns:xlink="http://www.w3.org/1999/xlink"
|
||||
id="0"
|
||||
class="displacy"
|
||||
width="1275"
|
||||
height="399.5"
|
||||
style="
|
||||
max-width: none;
|
||||
height: 399.5px;
|
||||
color: #000000;
|
||||
background: #ffffff;
|
||||
font-family: Arial;
|
||||
"
|
||||
>
|
||||
<text class="displacy-token" fill="currentColor" text-anchor="middle" y="309.5">
|
||||
<tspan class="displacy-word" fill="currentColor" x="50">Autonomous</tspan>
|
||||
<tspan class="displacy-tag" dy="2em" fill="currentColor" x="50">ADJ</tspan>
|
||||
</text>
|
||||
<path class="displacy-arrowhead" d="M70,266.5 L62,254.5 78,254.5" fill="currentColor"></path>
|
||||
</g>
|
||||
|
||||
<g class="displacy-arrow">
|
||||
<path class="displacy-arc" id="arrow-0-1" stroke-width="2px" d="M245,264.5 C245,177.0 390.0,177.0 390.0,264.5" fill="none" stroke="currentColor"></path>
|
||||
<text dy="1.25em" style="font-size: 0.8em; letter-spacing: 1px">
|
||||
<textpath xlink:href="#arrow-0-1" class="displacy-label" startOffset="50%" fill="currentColor" text-anchor="middle">nsubj</textpath>
|
||||
<text class="displacy-token" fill="currentColor" text-anchor="middle" y="309.5">
|
||||
<tspan class="displacy-word" fill="currentColor" x="225">cars</tspan>
|
||||
<tspan class="displacy-tag" dy="2em" fill="currentColor" x="225">NOUN</tspan>
|
||||
</text>
|
||||
<path class="displacy-arrowhead" d="M245,266.5 L237,254.5 253,254.5" fill="currentColor"></path>
|
||||
</g>
|
||||
|
||||
<g class="displacy-arrow">
|
||||
<path class="displacy-arc" id="arrow-0-2" stroke-width="2px" d="M595,264.5 C595,177.0 740.0,177.0 740.0,264.5" fill="none" stroke="currentColor"></path>
|
||||
<text dy="1.25em" style="font-size: 0.8em; letter-spacing: 1px">
|
||||
<textpath xlink:href="#arrow-0-2" class="displacy-label" startOffset="50%" fill="currentColor" text-anchor="middle">compound</textpath>
|
||||
<text class="displacy-token" fill="currentColor" text-anchor="middle" y="309.5">
|
||||
<tspan class="displacy-word" fill="currentColor" x="400">shift</tspan>
|
||||
<tspan class="displacy-tag" dy="2em" fill="currentColor" x="400">VERB</tspan>
|
||||
</text>
|
||||
<path class="displacy-arrowhead" d="M595,266.5 L587,254.5 603,254.5" fill="currentColor"></path>
|
||||
</g>
|
||||
|
||||
<g class="displacy-arrow">
|
||||
<path class="displacy-arc" id="arrow-0-3" stroke-width="2px" d="M420,264.5 C420,89.5 745.0,89.5 745.0,264.5" fill="none" stroke="currentColor"></path>
|
||||
<text dy="1.25em" style="font-size: 0.8em; letter-spacing: 1px">
|
||||
<textpath xlink:href="#arrow-0-3" class="displacy-label" startOffset="50%" fill="currentColor" text-anchor="middle">dobj</textpath>
|
||||
<text class="displacy-token" fill="currentColor" text-anchor="middle" y="309.5">
|
||||
<tspan class="displacy-word" fill="currentColor" x="575">insurance</tspan>
|
||||
<tspan class="displacy-tag" dy="2em" fill="currentColor" x="575">NOUN</tspan>
|
||||
</text>
|
||||
<path class="displacy-arrowhead" d="M745.0,266.5 L753.0,254.5 737.0,254.5" fill="currentColor"></path>
|
||||
</g>
|
||||
|
||||
<g class="displacy-arrow">
|
||||
<path class="displacy-arc" id="arrow-0-4" stroke-width="2px" d="M420,264.5 C420,2.0 925.0,2.0 925.0,264.5" fill="none" stroke="currentColor"></path>
|
||||
<text dy="1.25em" style="font-size: 0.8em; letter-spacing: 1px">
|
||||
<textpath xlink:href="#arrow-0-4" class="displacy-label" startOffset="50%" fill="currentColor" text-anchor="middle">prep</textpath>
|
||||
<text class="displacy-token" fill="currentColor" text-anchor="middle" y="309.5">
|
||||
<tspan class="displacy-word" fill="currentColor" x="750">liability</tspan>
|
||||
<tspan class="displacy-tag" dy="2em" fill="currentColor" x="750">NOUN</tspan>
|
||||
</text>
|
||||
<path class="displacy-arrowhead" d="M925.0,266.5 L933.0,254.5 917.0,254.5" fill="currentColor"></path>
|
||||
</g>
|
||||
|
||||
<g class="displacy-arrow">
|
||||
<path class="displacy-arc" id="arrow-0-5" stroke-width="2px" d="M945,264.5 C945,177.0 1090.0,177.0 1090.0,264.5" fill="none" stroke="currentColor"></path>
|
||||
<text dy="1.25em" style="font-size: 0.8em; letter-spacing: 1px">
|
||||
<textpath xlink:href="#arrow-0-5" class="displacy-label" startOffset="50%" fill="currentColor" text-anchor="middle">pobj</textpath>
|
||||
<text class="displacy-token" fill="currentColor" text-anchor="middle" y="309.5">
|
||||
<tspan class="displacy-word" fill="currentColor" x="925">toward</tspan>
|
||||
<tspan class="displacy-tag" dy="2em" fill="currentColor" x="925">ADP</tspan>
|
||||
</text>
|
||||
<path class="displacy-arrowhead" d="M1090.0,266.5 L1098.0,254.5 1082.0,254.5" fill="currentColor"></path>
|
||||
</g>
|
||||
|
||||
<text class="displacy-token" fill="currentColor" text-anchor="middle" y="309.5">
|
||||
<tspan class="displacy-word" fill="currentColor" x="1100">manufacturers</tspan>
|
||||
<tspan class="displacy-tag" dy="2em" fill="currentColor" x="1100">NOUN</tspan>
|
||||
</text>
|
||||
|
||||
<g class="displacy-arrow">
|
||||
<path
|
||||
class="displacy-arc"
|
||||
id="arrow-0-0"
|
||||
stroke-width="2px"
|
||||
d="M70,264.5 C70,177.0 215.0,177.0 215.0,264.5"
|
||||
fill="none"
|
||||
stroke="currentColor"
|
||||
></path>
|
||||
<text dy="1.25em" style="font-size: 0.8em; letter-spacing: 1px">
|
||||
<textpath
|
||||
xlink:href="#arrow-0-0"
|
||||
class="displacy-label"
|
||||
startOffset="50%"
|
||||
fill="currentColor"
|
||||
text-anchor="middle"
|
||||
>
|
||||
amod
|
||||
</textpath>
|
||||
</text>
|
||||
<path
|
||||
class="displacy-arrowhead"
|
||||
d="M70,266.5 L62,254.5 78,254.5"
|
||||
fill="currentColor"
|
||||
></path>
|
||||
</g>
|
||||
|
||||
<g class="displacy-arrow">
|
||||
<path
|
||||
class="displacy-arc"
|
||||
id="arrow-0-1"
|
||||
stroke-width="2px"
|
||||
d="M245,264.5 C245,177.0 390.0,177.0 390.0,264.5"
|
||||
fill="none"
|
||||
stroke="currentColor"
|
||||
></path>
|
||||
<text dy="1.25em" style="font-size: 0.8em; letter-spacing: 1px">
|
||||
<textpath
|
||||
xlink:href="#arrow-0-1"
|
||||
class="displacy-label"
|
||||
startOffset="50%"
|
||||
fill="currentColor"
|
||||
text-anchor="middle"
|
||||
>
|
||||
nsubj
|
||||
</textpath>
|
||||
</text>
|
||||
<path
|
||||
class="displacy-arrowhead"
|
||||
d="M245,266.5 L237,254.5 253,254.5"
|
||||
fill="currentColor"
|
||||
></path>
|
||||
</g>
|
||||
|
||||
<g class="displacy-arrow">
|
||||
<path
|
||||
class="displacy-arc"
|
||||
id="arrow-0-2"
|
||||
stroke-width="2px"
|
||||
d="M595,264.5 C595,177.0 740.0,177.0 740.0,264.5"
|
||||
fill="none"
|
||||
stroke="currentColor"
|
||||
></path>
|
||||
<text dy="1.25em" style="font-size: 0.8em; letter-spacing: 1px">
|
||||
<textpath
|
||||
xlink:href="#arrow-0-2"
|
||||
class="displacy-label"
|
||||
startOffset="50%"
|
||||
fill="currentColor"
|
||||
text-anchor="middle"
|
||||
>
|
||||
compound
|
||||
</textpath>
|
||||
</text>
|
||||
<path
|
||||
class="displacy-arrowhead"
|
||||
d="M595,266.5 L587,254.5 603,254.5"
|
||||
fill="currentColor"
|
||||
></path>
|
||||
</g>
|
||||
|
||||
<g class="displacy-arrow">
|
||||
<path
|
||||
class="displacy-arc"
|
||||
id="arrow-0-3"
|
||||
stroke-width="2px"
|
||||
d="M420,264.5 C420,89.5 745.0,89.5 745.0,264.5"
|
||||
fill="none"
|
||||
stroke="currentColor"
|
||||
></path>
|
||||
<text dy="1.25em" style="font-size: 0.8em; letter-spacing: 1px">
|
||||
<textpath
|
||||
xlink:href="#arrow-0-3"
|
||||
class="displacy-label"
|
||||
startOffset="50%"
|
||||
fill="currentColor"
|
||||
text-anchor="middle"
|
||||
>
|
||||
dobj
|
||||
</textpath>
|
||||
</text>
|
||||
<path
|
||||
class="displacy-arrowhead"
|
||||
d="M745.0,266.5 L753.0,254.5 737.0,254.5"
|
||||
fill="currentColor"
|
||||
></path>
|
||||
</g>
|
||||
|
||||
<g class="displacy-arrow">
|
||||
<path
|
||||
class="displacy-arc"
|
||||
id="arrow-0-4"
|
||||
stroke-width="2px"
|
||||
d="M420,264.5 C420,2.0 925.0,2.0 925.0,264.5"
|
||||
fill="none"
|
||||
stroke="currentColor"
|
||||
></path>
|
||||
<text dy="1.25em" style="font-size: 0.8em; letter-spacing: 1px">
|
||||
<textpath
|
||||
xlink:href="#arrow-0-4"
|
||||
class="displacy-label"
|
||||
startOffset="50%"
|
||||
fill="currentColor"
|
||||
text-anchor="middle"
|
||||
>
|
||||
prep
|
||||
</textpath>
|
||||
</text>
|
||||
<path
|
||||
class="displacy-arrowhead"
|
||||
d="M925.0,266.5 L933.0,254.5 917.0,254.5"
|
||||
fill="currentColor"
|
||||
></path>
|
||||
</g>
|
||||
|
||||
<g class="displacy-arrow">
|
||||
<path
|
||||
class="displacy-arc"
|
||||
id="arrow-0-5"
|
||||
stroke-width="2px"
|
||||
d="M945,264.5 C945,177.0 1090.0,177.0 1090.0,264.5"
|
||||
fill="none"
|
||||
stroke="currentColor"
|
||||
></path>
|
||||
<text dy="1.25em" style="font-size: 0.8em; letter-spacing: 1px">
|
||||
<textpath
|
||||
xlink:href="#arrow-0-5"
|
||||
class="displacy-label"
|
||||
startOffset="50%"
|
||||
fill="currentColor"
|
||||
text-anchor="middle"
|
||||
>
|
||||
pobj
|
||||
</textpath>
|
||||
</text>
|
||||
<path
|
||||
class="displacy-arrowhead"
|
||||
d="M1090.0,266.5 L1098.0,254.5 1082.0,254.5"
|
||||
fill="currentColor"
|
||||
></path>
|
||||
</g>
|
||||
</svg>
|
||||
|
|
|
|||
|
Before Width: | Height: | Size: 5.0 KiB After Width: | Height: | Size: 6.8 KiB |
|
|
@ -1,31 +1,84 @@
|
|||
<div class="spans"
|
||||
style="line-height: 2.5; font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Helvetica, Arial, sans-serif, 'Apple Color Emoji', 'Segoe UI Emoji', 'Segoe UI Symbol'; font-size: 18px; direction: ltr">
|
||||
<div
|
||||
class="spans"
|
||||
style="
|
||||
line-height: 2.5;
|
||||
font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Helvetica, Arial, sans-serif,
|
||||
'Apple Color Emoji', 'Segoe UI Emoji', 'Segoe UI Symbol';
|
||||
font-size: 18px;
|
||||
direction: ltr;
|
||||
"
|
||||
>
|
||||
Welcome to the
|
||||
<span style="font-weight: bold; display: inline-block; position: relative;">
|
||||
<span style="font-weight: bold; display: inline-block; position: relative">
|
||||
Bank
|
||||
<span
|
||||
style="background: #ddd; top: 40px; height: 4px; left: -1px; width: calc(100% + 2px); position: absolute;">
|
||||
style="
|
||||
background: #ddd;
|
||||
top: 40px;
|
||||
height: 4px;
|
||||
left: -1px;
|
||||
width: calc(100% + 2px);
|
||||
position: absolute;
|
||||
"
|
||||
>
|
||||
</span>
|
||||
<span
|
||||
style="background: #ddd; top: 40px; height: 4px; border-top-left-radius: 3px; border-bottom-left-radius: 3px; left: -1px; width: calc(100% + 2px); position: absolute;">
|
||||
style="
|
||||
background: #ddd;
|
||||
top: 40px;
|
||||
height: 4px;
|
||||
border-top-left-radius: 3px;
|
||||
border-bottom-left-radius: 3px;
|
||||
left: -1px;
|
||||
width: calc(100% + 2px);
|
||||
position: absolute;
|
||||
"
|
||||
>
|
||||
<span
|
||||
style="background: #ddd; color: #000; top: -0.5em; padding: 2px 3px; position: absolute; font-size: 0.6em; font-weight: bold; line-height: 1; border-radius: 3px">
|
||||
style="
|
||||
background: #ddd;
|
||||
color: #000;
|
||||
top: -0.5em;
|
||||
padding: 2px 3px;
|
||||
position: absolute;
|
||||
font-size: 0.6em;
|
||||
font-weight: bold;
|
||||
line-height: 1;
|
||||
border-radius: 3px;
|
||||
"
|
||||
>
|
||||
BANK
|
||||
</span>
|
||||
</span>
|
||||
</span>
|
||||
<span style="font-weight: bold; display: inline-block; position: relative;">
|
||||
<span style="font-weight: bold; display: inline-block; position: relative">
|
||||
of
|
||||
<span
|
||||
style="background: #ddd; top: 40px; height: 4px; left: -1px; width: calc(100% + 2px); position: absolute;">
|
||||
style="
|
||||
background: #ddd;
|
||||
top: 40px;
|
||||
height: 4px;
|
||||
left: -1px;
|
||||
width: calc(100% + 2px);
|
||||
position: absolute;
|
||||
"
|
||||
>
|
||||
</span>
|
||||
</span>
|
||||
<span style="font-weight: bold; display: inline-block; position: relative;">
|
||||
<span style="font-weight: bold; display: inline-block; position: relative">
|
||||
China
|
||||
|
||||
<span
|
||||
style="background: #ddd; top: 40px; height: 4px; left: -1px; width: calc(100% + 2px); position: absolute;">
|
||||
style="
|
||||
background: #ddd;
|
||||
top: 40px;
|
||||
height: 4px;
|
||||
left: -1px;
|
||||
width: calc(100% + 2px);
|
||||
position: absolute;
|
||||
"
|
||||
>
|
||||
</span>
|
||||
</span>
|
||||
.
|
||||
</div>
|
||||
</div>
|
||||
|
|
|
|||
|
|
@ -1,41 +1,123 @@
|
|||
<div class="spans"
|
||||
style="line-height: 2.5; direction: ltr; font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Helvetica, Arial, sans-serif, 'Apple Color Emoji', 'Segoe UI Emoji', 'Segoe UI Symbol'; font-size: 18px">
|
||||
<div
|
||||
class="spans"
|
||||
style="
|
||||
line-height: 2.5;
|
||||
direction: ltr;
|
||||
font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Helvetica, Arial, sans-serif,
|
||||
'Apple Color Emoji', 'Segoe UI Emoji', 'Segoe UI Symbol';
|
||||
font-size: 18px;
|
||||
"
|
||||
>
|
||||
Welcome to the
|
||||
<span style="font-weight: bold; display: inline-block; position: relative;">
|
||||
<span style="font-weight: bold; display: inline-block; position: relative">
|
||||
Bank
|
||||
<span
|
||||
style="background: #7aecec; top: 40px; height: 4px; left: -1px; width: calc(100% + 2px); position: absolute;">
|
||||
style="
|
||||
background: #7aecec;
|
||||
top: 40px;
|
||||
height: 4px;
|
||||
left: -1px;
|
||||
width: calc(100% + 2px);
|
||||
position: absolute;
|
||||
"
|
||||
>
|
||||
</span>
|
||||
<span
|
||||
style="background: #7aecec; top: 40px; height: 4px; border-top-left-radius: 3px; border-bottom-left-radius: 3px; left: -1px; width: calc(100% + 2px); position: absolute;">
|
||||
style="
|
||||
background: #7aecec;
|
||||
top: 40px;
|
||||
height: 4px;
|
||||
border-top-left-radius: 3px;
|
||||
border-bottom-left-radius: 3px;
|
||||
left: -1px;
|
||||
width: calc(100% + 2px);
|
||||
position: absolute;
|
||||
"
|
||||
>
|
||||
<span
|
||||
style="background: #7aecec; color: #000; top: -0.5em; padding: 2px 3px; position: absolute; font-size: 0.6em; font-weight: bold; line-height: 1; border-radius: 3px">
|
||||
style="
|
||||
background: #7aecec;
|
||||
color: #000;
|
||||
top: -0.5em;
|
||||
padding: 2px 3px;
|
||||
position: absolute;
|
||||
font-size: 0.6em;
|
||||
font-weight: bold;
|
||||
line-height: 1;
|
||||
border-radius: 3px;
|
||||
"
|
||||
>
|
||||
ORG
|
||||
</span>
|
||||
</span>
|
||||
</span>
|
||||
<span style="font-weight: bold; display: inline-block; position: relative;">
|
||||
<span style="font-weight: bold; display: inline-block; position: relative">
|
||||
of
|
||||
|
||||
<span
|
||||
style="background: #7aecec; top: 40px; height: 4px; left: -1px; width: calc(100% + 2px); position: absolute;">
|
||||
style="
|
||||
background: #7aecec;
|
||||
top: 40px;
|
||||
height: 4px;
|
||||
left: -1px;
|
||||
width: calc(100% + 2px);
|
||||
position: absolute;
|
||||
"
|
||||
>
|
||||
</span>
|
||||
</span>
|
||||
<span style="font-weight: bold; display: inline-block; position: relative;">
|
||||
<span style="font-weight: bold; display: inline-block; position: relative">
|
||||
China
|
||||
<span
|
||||
style="background: #7aecec; top: 40px; height: 4px; left: -1px; width: calc(100% + 2px); position: absolute;">
|
||||
style="
|
||||
background: #7aecec;
|
||||
top: 40px;
|
||||
height: 4px;
|
||||
left: -1px;
|
||||
width: calc(100% + 2px);
|
||||
position: absolute;
|
||||
"
|
||||
>
|
||||
</span>
|
||||
<span
|
||||
style="background: #feca74; top: 57px; height: 4px; left: -1px; width: calc(100% + 2px); position: absolute;">
|
||||
style="
|
||||
background: #feca74;
|
||||
top: 57px;
|
||||
height: 4px;
|
||||
left: -1px;
|
||||
width: calc(100% + 2px);
|
||||
position: absolute;
|
||||
"
|
||||
>
|
||||
</span>
|
||||
<span
|
||||
style="background: #feca74; top: 57px; height: 4px; border-top-left-radius: 3px; border-bottom-left-radius: 3px; left: -1px; width: calc(100% + 2px); position: absolute;">
|
||||
style="
|
||||
background: #feca74;
|
||||
top: 57px;
|
||||
height: 4px;
|
||||
border-top-left-radius: 3px;
|
||||
border-bottom-left-radius: 3px;
|
||||
left: -1px;
|
||||
width: calc(100% + 2px);
|
||||
position: absolute;
|
||||
"
|
||||
>
|
||||
<span
|
||||
style="background: #feca74; color: #000; top: -0.5em; padding: 2px 3px; position: absolute; font-size: 0.6em; font-weight: bold; line-height: 1; border-radius: 3px">
|
||||
style="
|
||||
background: #feca74;
|
||||
color: #000;
|
||||
top: -0.5em;
|
||||
padding: 2px 3px;
|
||||
position: absolute;
|
||||
font-size: 0.6em;
|
||||
font-weight: bold;
|
||||
line-height: 1;
|
||||
border-radius: 3px;
|
||||
"
|
||||
>
|
||||
GPE
|
||||
</span>
|
||||
</span>
|
||||
</span>
|
||||
.
|
||||
</div>
|
||||
</div>
|
||||
|
|
|
|||
|
|
@ -189,8 +189,8 @@ than the rule-based `sentencizer`.
|
|||
|
||||
#### Switch from trainable lemmatizer to default lemmatizer
|
||||
|
||||
Since v3.3, a number of pipelines use a trainable lemmatizer. You can check whether
|
||||
the lemmatizer is trainable:
|
||||
Since v3.3, a number of pipelines use a trainable lemmatizer. You can check
|
||||
whether the lemmatizer is trainable:
|
||||
|
||||
```python
|
||||
nlp = spacy.load("de_core_web_sm")
|
||||
|
|
|
|||
|
|
@ -65,8 +65,16 @@ import { Colors, Patterns } from 'widgets/styleguide'
|
|||
|
||||
## Typography {#typography}
|
||||
|
||||
import { H1, H2, H3, H4, H5, Label, InlineList, Comment } from
|
||||
'components/typography'
|
||||
import {
|
||||
H1,
|
||||
H2,
|
||||
H3,
|
||||
H4,
|
||||
H5,
|
||||
Label,
|
||||
InlineList,
|
||||
Comment,
|
||||
} from 'components/typography'
|
||||
|
||||
> #### Markdown
|
||||
>
|
||||
|
|
@ -101,12 +109,12 @@ in the sidebar menu.
|
|||
</Infobox>
|
||||
|
||||
<div>
|
||||
<H1>Headline 1</H1>
|
||||
<H2>Headline 2</H2>
|
||||
<H3>Headline 3</H3>
|
||||
<H4>Headline 4</H4>
|
||||
<H5>Headline 5</H5>
|
||||
<Label>Label</Label>
|
||||
<H1>Headline 1</H1>
|
||||
<H2>Headline 2</H2>
|
||||
<H3>Headline 3</H3>
|
||||
<H4>Headline 4</H4>
|
||||
<H5>Headline 5</H5>
|
||||
<Label>Label</Label>
|
||||
</div>
|
||||
|
||||
---
|
||||
|
|
@ -182,8 +190,9 @@ installed.
|
|||
|
||||
<InlineList>
|
||||
|
||||
<Tag>method</Tag> <Tag variant="new">4</Tag> <Tag variant="model">tagger,
|
||||
parser</Tag>
|
||||
<Tag>method</Tag> <Tag variant="new">4</Tag> <Tag variant="model">
|
||||
tagger, parser
|
||||
</Tag>
|
||||
|
||||
</InlineList>
|
||||
|
||||
|
|
@ -200,13 +209,25 @@ Link buttons come in two variants, `primary` and `secondary` and two sizes, with
|
|||
an optional `large` size modifier. Since they're mostly used as enhanced links,
|
||||
the buttons are implemented as styled links instead of native button elements.
|
||||
|
||||
<InlineList><Button to="#" variant="primary">Primary small</Button>
|
||||
<Button to="#" variant="secondary">Secondary small</Button></InlineList>
|
||||
<InlineList>
|
||||
<Button to="#" variant="primary">
|
||||
Primary small
|
||||
</Button>
|
||||
<Button to="#" variant="secondary">
|
||||
Secondary small
|
||||
</Button>
|
||||
</InlineList>
|
||||
|
||||
<br />
|
||||
|
||||
<InlineList><Button to="#" variant="primary" large>Primary large</Button>
|
||||
<Button to="#" variant="secondary" large>Secondary large</Button></InlineList>
|
||||
<InlineList>
|
||||
<Button to="#" variant="primary" large>
|
||||
Primary large
|
||||
</Button>
|
||||
<Button to="#" variant="secondary" large>
|
||||
Secondary large
|
||||
</Button>
|
||||
</InlineList>
|
||||
|
||||
## Components
|
||||
|
||||
|
|
|
|||
|
|
@ -1,9 +1,9 @@
|
|||
A named entity is a "real-world object" that's assigned a name – for example, a
|
||||
person, a country, a product or a book title. spaCy can **recognize various
|
||||
types of named entities in a document, by asking the model for a
|
||||
prediction**. Because models are statistical and strongly depend on the
|
||||
examples they were trained on, this doesn't always work _perfectly_ and might
|
||||
need some tuning later, depending on your use case.
|
||||
types of named entities in a document, by asking the model for a prediction**.
|
||||
Because models are statistical and strongly depend on the examples they were
|
||||
trained on, this doesn't always work _perfectly_ and might need some tuning
|
||||
later, depending on your use case.
|
||||
|
||||
Named entities are available as the `ents` property of a `Doc`:
|
||||
|
||||
|
|
@ -32,7 +32,11 @@ for ent in doc.ents:
|
|||
Using spaCy's built-in [displaCy visualizer](/usage/visualizers), here's what
|
||||
our example sentence and its named entities look like:
|
||||
|
||||
import DisplaCyEntHtml from 'images/displacy-ent1.html'; import { Iframe } from
|
||||
'components/embed'
|
||||
import DisplaCyEntHtml from 'images/displacy-ent1.html'
|
||||
import { Iframe } from 'components/embed'
|
||||
|
||||
<Iframe title="displaCy visualization of entities" html={DisplaCyEntHtml} height={100} />
|
||||
<Iframe
|
||||
title="displaCy visualization of entities"
|
||||
html={DisplaCyEntHtml}
|
||||
height={100}
|
||||
/>
|
||||
|
|
|
|||
|
|
@ -57,7 +57,11 @@ for token in doc:
|
|||
Using spaCy's built-in [displaCy visualizer](/usage/visualizers), here's what
|
||||
our example sentence and its dependencies look like:
|
||||
|
||||
import DisplaCyLongHtml from 'images/displacy-long.html'; import { Iframe } from
|
||||
'components/embed'
|
||||
import DisplaCyLongHtml from 'images/displacy-long.html'
|
||||
import { Iframe } from 'components/embed'
|
||||
|
||||
<Iframe title="displaCy visualization of dependencies and entities" html={DisplaCyLongHtml} height={450} />
|
||||
<Iframe
|
||||
title="displaCy visualization of dependencies and entities"
|
||||
html={DisplaCyLongHtml}
|
||||
height={450}
|
||||
/>
|
||||
|
|
|
|||
|
|
@ -10,9 +10,9 @@ any other information.
|
|||
Training is an iterative process in which the model's predictions are compared
|
||||
against the reference annotations in order to estimate the **gradient of the
|
||||
loss**. The gradient of the loss is then used to calculate the gradient of the
|
||||
weights through [backpropagation](https://thinc.ai/docs/backprop101). The gradients
|
||||
indicate how the weight values should be changed so that the model's predictions
|
||||
become more similar to the reference labels over time.
|
||||
weights through [backpropagation](https://thinc.ai/docs/backprop101). The
|
||||
gradients indicate how the weight values should be changed so that the model's
|
||||
predictions become more similar to the reference labels over time.
|
||||
|
||||
> - **Training data:** Examples and their annotations.
|
||||
> - **Text:** The input text the model should predict a label for.
|
||||
|
|
|
|||
|
|
@ -1,4 +1,5 @@
|
|||
import { Help } from 'components/typography'; import Link from 'components/link'
|
||||
import { Help } from 'components/typography'
|
||||
import Link from 'components/link'
|
||||
|
||||
<figure>
|
||||
|
||||
|
|
|
|||
|
|
@ -218,8 +218,8 @@ $ pip install torch==1.11.0+cu113 torchvision==0.12.0+cu113 torchaudio==0.11.0+c
|
|||
|
||||
Next, install spaCy with the extras for your CUDA version and transformers. The
|
||||
CUDA extra (e.g., `cuda102`, `cuda113`) installs the correct version of
|
||||
[`cupy`](https://docs.cupy.dev/en/stable/install.html#installing-cupy), which
|
||||
is just like `numpy`, but for GPU. You may also need to set the `CUDA_PATH`
|
||||
[`cupy`](https://docs.cupy.dev/en/stable/install.html#installing-cupy), which is
|
||||
just like `numpy`, but for GPU. You may also need to set the `CUDA_PATH`
|
||||
environment variable if your CUDA runtime is installed in a non-standard
|
||||
location. Putting it all together, if you had installed CUDA 11.3 in
|
||||
`/opt/nvidia/cuda`, you would run:
|
||||
|
|
@ -531,8 +531,7 @@ Word vectors in spaCy are "static" in the sense that they are not learned
|
|||
parameters of the statistical models, and spaCy itself does not feature any
|
||||
algorithms for learning word vector tables. You can train a word vectors table
|
||||
using tools such as [floret](https://github.com/explosion/floret),
|
||||
[Gensim](https://radimrehurek.com/gensim/),
|
||||
[FastText](https://fasttext.cc/) or
|
||||
[Gensim](https://radimrehurek.com/gensim/), [FastText](https://fasttext.cc/) or
|
||||
[GloVe](https://nlp.stanford.edu/projects/glove/), or download existing
|
||||
pretrained vectors. The [`init vectors`](/api/cli#init-vectors) command lets you
|
||||
convert vectors for use with spaCy and will give you a directory you can load or
|
||||
|
|
|
|||
|
|
@ -69,7 +69,7 @@ pipeline, which is less accurate but much cheaper to run.
|
|||
> gold-standard segmentation and tokenization, from a pretty specific type of
|
||||
> text (articles from a single newspaper, 1984-1989).
|
||||
|
||||
import Benchmarks from 'usage/\_benchmarks-models.mdx'
|
||||
import Benchmarks from 'usage/_benchmarks-models.mdx'
|
||||
|
||||
<Benchmarks />
|
||||
|
||||
|
|
|
|||
|
|
@ -181,7 +181,9 @@ $ pip install --no-build-isolation --editable .[lookups,cuda102]
|
|||
|
||||
How to install compilers and related build tools:
|
||||
|
||||
<a id="source-ubuntu"></a><a id="source-osx"></a><a id="source-windows"></a>
|
||||
<a id="source-ubuntu"></a>
|
||||
<a id="source-osx"></a>
|
||||
<a id="source-windows"></a>
|
||||
|
||||
- **Ubuntu:** Install system-level dependencies via `apt-get`:
|
||||
`sudo apt-get install build-essential python-dev git`
|
||||
|
|
@ -235,10 +237,10 @@ package to see what the oldest recommended versions of `numpy` are.
|
|||
Some additional options may be useful for spaCy developers who are editing the
|
||||
source code and recompiling frequently.
|
||||
|
||||
- Install in editable mode. Changes to `.py` files will be reflected as soon
|
||||
as the files are saved, but edits to Cython files (`.pxd`, `.pyx`) will
|
||||
require the `pip install` command below to be run again. Before installing in
|
||||
editable mode, be sure you have removed any previous installs with
|
||||
- Install in editable mode. Changes to `.py` files will be reflected as soon as
|
||||
the files are saved, but edits to Cython files (`.pxd`, `.pyx`) will require
|
||||
the `pip install` command below to be run again. Before installing in editable
|
||||
mode, be sure you have removed any previous installs with
|
||||
`pip uninstall spacy`, which you may need to run multiple times to remove all
|
||||
traces of earlier installs.
|
||||
|
||||
|
|
@ -247,8 +249,8 @@ source code and recompiling frequently.
|
|||
$ pip install --no-build-isolation --editable .
|
||||
```
|
||||
|
||||
- Build in parallel. Starting in v3.4.0, you can specify the number of
|
||||
build jobs with the environment variable `SPACY_NUM_BUILD_JOBS`:
|
||||
- Build in parallel. Starting in v3.4.0, you can specify the number of build
|
||||
jobs with the environment variable `SPACY_NUM_BUILD_JOBS`:
|
||||
|
||||
```bash
|
||||
$ pip install -r requirements.txt
|
||||
|
|
|
|||
|
|
@ -537,13 +537,13 @@ two major steps required:
|
|||
pass through the `nlp` pipeline.
|
||||
|
||||
<Project id="tutorials/rel_component">
|
||||
Run this example use-case by using our project template. It includes all the
|
||||
code to create the ML model and the pipeline component from scratch.
|
||||
It also contains two config files to train the model:
|
||||
one to run on CPU with a Tok2Vec layer, and one for the GPU using a transformer.
|
||||
The project applies the relation extraction component to identify biomolecular
|
||||
interactions in a sample dataset, but you can easily swap in your own dataset
|
||||
for your experiments in any other domain.
|
||||
Run this example use-case by using our project template. It includes all the
|
||||
code to create the ML model and the pipeline component from scratch. It also
|
||||
contains two config files to train the model: one to run on CPU with a Tok2Vec
|
||||
layer, and one for the GPU using a transformer. The project applies the
|
||||
relation extraction component to identify biomolecular interactions in a
|
||||
sample dataset, but you can easily swap in your own dataset for your
|
||||
experiments in any other domain.
|
||||
</Project>
|
||||
|
||||
<YouTube id="8HL-Ap5_Axo"></YouTube>
|
||||
|
|
@ -1043,11 +1043,10 @@ def make_relation_extractor(nlp, name, model):
|
|||
```
|
||||
|
||||
<Project id="tutorials/rel_component">
|
||||
Run this example use-case by using our project template. It includes all the
|
||||
code to create the ML model and the pipeline component from scratch.
|
||||
It contains two config files to train the model:
|
||||
one to run on CPU with a Tok2Vec layer, and one for the GPU using a transformer.
|
||||
The project applies the relation extraction component to identify biomolecular
|
||||
interactions, but you can easily swap in your own dataset for your experiments
|
||||
in any other domain.
|
||||
Run this example use-case by using our project template. It includes all the
|
||||
code to create the ML model and the pipeline component from scratch. It
|
||||
contains two config files to train the model: one to run on CPU with a Tok2Vec
|
||||
layer, and one for the GPU using a transformer. The project applies the
|
||||
relation extraction component to identify biomolecular interactions, but you
|
||||
can easily swap in your own dataset for your experiments in any other domain.
|
||||
</Project>
|
||||
|
|
|
|||
|
|
@ -28,7 +28,7 @@ annotations.
|
|||
|
||||
## Part-of-speech tagging {#pos-tagging model="tagger, parser"}
|
||||
|
||||
import PosDeps101 from 'usage/101/\_pos-deps.mdx'
|
||||
import PosDeps101 from 'usage/101/_pos-deps.mdx'
|
||||
|
||||
<PosDeps101 />
|
||||
|
||||
|
|
@ -300,7 +300,11 @@ for token in doc:
|
|||
|
||||
import DisplaCyLong2Html from 'images/displacy-long2.html'
|
||||
|
||||
<Iframe title="displaCy visualization of dependencies and entities 2" html={DisplaCyLong2Html} height={450} />
|
||||
<Iframe
|
||||
title="displaCy visualization of dependencies and entities 2"
|
||||
html={DisplaCyLong2Html}
|
||||
height={450}
|
||||
/>
|
||||
|
||||
Because the syntactic relations form a tree, every word has **exactly one
|
||||
head**. You can therefore iterate over the arcs in the tree by iterating over
|
||||
|
|
@ -536,7 +540,7 @@ with new examples.
|
|||
|
||||
### Named Entity Recognition 101 {#named-entities-101}
|
||||
|
||||
import NER101 from 'usage/101/\_named-entities.mdx'
|
||||
import NER101 from 'usage/101/_named-entities.mdx'
|
||||
|
||||
<NER101 />
|
||||
|
||||
|
|
@ -730,7 +734,11 @@ displacy.serve(doc, style="ent")
|
|||
|
||||
import DisplacyEntHtml from 'images/displacy-ent2.html'
|
||||
|
||||
<Iframe title="displaCy visualizer for entities" html={DisplacyEntHtml} height={180} />
|
||||
<Iframe
|
||||
title="displaCy visualizer for entities"
|
||||
html={DisplacyEntHtml}
|
||||
height={180}
|
||||
/>
|
||||
|
||||
## Entity Linking {#entity-linking}
|
||||
|
||||
|
|
@ -785,7 +793,7 @@ during tokenization. This is kind of a core principle of spaCy's `Doc` object:
|
|||
|
||||
</Infobox>
|
||||
|
||||
import Tokenization101 from 'usage/101/\_tokenization.mdx'
|
||||
import Tokenization101 from 'usage/101/_tokenization.mdx'
|
||||
|
||||
<Tokenization101 />
|
||||
|
||||
|
|
@ -1868,7 +1876,7 @@ initialized before training. See the
|
|||
|
||||
## Word vectors and semantic similarity {#vectors-similarity}
|
||||
|
||||
import Vectors101 from 'usage/101/\_vectors-similarity.mdx'
|
||||
import Vectors101 from 'usage/101/_vectors-similarity.mdx'
|
||||
|
||||
<Vectors101 />
|
||||
|
||||
|
|
@ -1998,7 +2006,7 @@ for word, vector in vector_data.items():
|
|||
|
||||
## Language Data {#language-data}
|
||||
|
||||
import LanguageData101 from 'usage/101/\_language-data.mdx'
|
||||
import LanguageData101 from 'usage/101/_language-data.mdx'
|
||||
|
||||
<LanguageData101 />
|
||||
|
||||
|
|
|
|||
|
|
@ -25,7 +25,11 @@ located anywhere on your file system.
|
|||
|
||||
import QuickstartModels from 'widgets/quickstart-models.js'
|
||||
|
||||
<QuickstartModels title="Quickstart" id="quickstart" description="Install a default trained pipeline package, get the code to load it from within spaCy and an example to test it. For more options, see the section on available packages below." />
|
||||
<QuickstartModels
|
||||
title="Quickstart"
|
||||
id="quickstart"
|
||||
description="Install a default trained pipeline package, get the code to load it from within spaCy and an example to test it. For more options, see the section on available packages below."
|
||||
/>
|
||||
|
||||
### Usage note
|
||||
|
||||
|
|
|
|||
|
|
@ -12,7 +12,7 @@ menu:
|
|||
- ['Plugins & Wrappers', 'plugins']
|
||||
---
|
||||
|
||||
import Pipelines101 from 'usage/101/\_pipelines.mdx'
|
||||
import Pipelines101 from 'usage/101/_pipelines.mdx'
|
||||
|
||||
<Pipelines101 />
|
||||
|
||||
|
|
@ -364,7 +364,8 @@ nlp.enable_pipe("tagger")
|
|||
|
||||
In addition to `disable`, `spacy.load()` also accepts `enable`. If `enable` is
|
||||
set, all components except for those in `enable` are disabled. If `enable` and
|
||||
`disable` conflict (i.e. the same component is included in both), an error is raised.
|
||||
`disable` conflict (i.e. the same component is included in both), an error is
|
||||
raised.
|
||||
|
||||
```python
|
||||
# Load the complete pipeline, but disable all components except for tok2vec and tagger
|
||||
|
|
|
|||
|
|
@ -43,13 +43,31 @@ and experiments, iterate on demos and prototypes and ship your models into
|
|||
production.
|
||||
|
||||
<Grid narrow cols={3}>
|
||||
<Integration title="DVC" logo="dvc" url="#dvc">Manage and version your data</Integration>
|
||||
<Integration title="Prodigy" logo="prodigy" url="#prodigy">Create labelled training data</Integration>
|
||||
<Integration title="Streamlit" logo="streamlit" url="#streamlit">Visualize and demo your pipelines</Integration>
|
||||
<Integration title="FastAPI" logo="fastapi" url="#fastapi">Serve your models and host APIs</Integration>
|
||||
<Integration title="Ray" logo="ray" url="#ray">Distributed and parallel training</Integration>
|
||||
<Integration title="Weights & Biases" logo="wandb" url="#wandb">Track your experiments and results</Integration>
|
||||
<Integration title="Hugging Face Hub" logo="huggingface_hub" url="#huggingface_hub">Upload your pipelines to the Hugging Face Hub</Integration>
|
||||
<Integration title="DVC" logo="dvc" url="#dvc">
|
||||
Manage and version your data
|
||||
</Integration>
|
||||
<Integration title="Prodigy" logo="prodigy" url="#prodigy">
|
||||
Create labelled training data
|
||||
</Integration>
|
||||
<Integration title="Streamlit" logo="streamlit" url="#streamlit">
|
||||
Visualize and demo your pipelines
|
||||
</Integration>
|
||||
<Integration title="FastAPI" logo="fastapi" url="#fastapi">
|
||||
Serve your models and host APIs
|
||||
</Integration>
|
||||
<Integration title="Ray" logo="ray" url="#ray">
|
||||
Distributed and parallel training
|
||||
</Integration>
|
||||
<Integration title="Weights & Biases" logo="wandb" url="#wandb">
|
||||
Track your experiments and results
|
||||
</Integration>
|
||||
<Integration
|
||||
title="Hugging Face Hub"
|
||||
logo="huggingface_hub"
|
||||
url="#huggingface_hub"
|
||||
>
|
||||
Upload your pipelines to the Hugging Face Hub
|
||||
</Integration>
|
||||
</Grid>
|
||||
|
||||
### 1. Clone a project template {#clone}
|
||||
|
|
|
|||
|
|
@ -1107,7 +1107,11 @@ relations and tokens we want to match:
|
|||
|
||||
import DisplaCyDepFoundedHtml from 'images/displacy-dep-founded.html'
|
||||
|
||||
<Iframe title="displaCy visualization of dependencies" html={DisplaCyDepFoundedHtml} height={450} />
|
||||
<Iframe
|
||||
title="displaCy visualization of dependencies"
|
||||
html={DisplaCyDepFoundedHtml}
|
||||
height={450}
|
||||
/>
|
||||
|
||||
The relations we're interested in are:
|
||||
|
||||
|
|
|
|||
|
|
@ -10,7 +10,7 @@ menu:
|
|||
|
||||
## Basics {#basics hidden="true"}
|
||||
|
||||
import Serialization101 from 'usage/101/\_serialization.mdx'
|
||||
import Serialization101 from 'usage/101/_serialization.mdx'
|
||||
|
||||
<Serialization101 />
|
||||
|
||||
|
|
@ -582,7 +582,11 @@ displayed in `#3dff74`.
|
|||
|
||||
import DisplaCyEntSnekHtml from 'images/displacy-ent-snek.html'
|
||||
|
||||
<Iframe title="displaCy visualization of entities" html={DisplaCyEntSnekHtml} height={100} />
|
||||
<Iframe
|
||||
title="displaCy visualization of entities"
|
||||
html={DisplaCyEntSnekHtml}
|
||||
height={100}
|
||||
/>
|
||||
|
||||
## Saving, loading and distributing trained pipelines {#models}
|
||||
|
||||
|
|
|
|||
|
|
@ -37,7 +37,11 @@ understanding systems, using both rule-based and machine learning approaches. It
|
|||
includes 55 exercises featuring interactive coding practice, multiple-choice
|
||||
questions and slide decks.
|
||||
|
||||
<p><Button to="https://course.spacy.io" variant="primary">Start the course</Button></p>
|
||||
<p>
|
||||
<Button to="https://course.spacy.io" variant="primary">
|
||||
Start the course
|
||||
</Button>
|
||||
</p>
|
||||
|
||||
</Infobox>
|
||||
|
||||
|
|
@ -191,7 +195,7 @@ text with spaCy.
|
|||
|
||||
### Tokenization {#annotations-token}
|
||||
|
||||
import Tokenization101 from 'usage/101/\_tokenization.mdx'
|
||||
import Tokenization101 from 'usage/101/_tokenization.mdx'
|
||||
|
||||
<Tokenization101 />
|
||||
|
||||
|
|
@ -207,7 +211,7 @@ language-specific data**, see the usage guides on
|
|||
|
||||
### Part-of-speech tags and dependencies {#annotations-pos-deps model="parser"}
|
||||
|
||||
import PosDeps101 from 'usage/101/\_pos-deps.mdx'
|
||||
import PosDeps101 from 'usage/101/_pos-deps.mdx'
|
||||
|
||||
<PosDeps101 />
|
||||
|
||||
|
|
@ -222,7 +226,7 @@ how to **navigate and use the parse tree** effectively, see the usage guides on
|
|||
|
||||
### Named Entities {#annotations-ner model="ner"}
|
||||
|
||||
import NER101 from 'usage/101/\_named-entities.mdx'
|
||||
import NER101 from 'usage/101/_named-entities.mdx'
|
||||
|
||||
<NER101 />
|
||||
|
||||
|
|
@ -238,7 +242,7 @@ of a model, see the usage guides on
|
|||
|
||||
### Word vectors and similarity {#vectors-similarity model="vectors"}
|
||||
|
||||
import Vectors101 from 'usage/101/\_vectors-similarity.mdx'
|
||||
import Vectors101 from 'usage/101/_vectors-similarity.mdx'
|
||||
|
||||
<Vectors101 />
|
||||
|
||||
|
|
@ -252,7 +256,7 @@ To learn more about word vectors, how to **customize them** and how to load
|
|||
|
||||
## Pipelines {#pipelines}
|
||||
|
||||
import Pipelines101 from 'usage/101/\_pipelines.mdx'
|
||||
import Pipelines101 from 'usage/101/_pipelines.mdx'
|
||||
|
||||
<Pipelines101 />
|
||||
|
||||
|
|
@ -266,7 +270,7 @@ guide on [language processing pipelines](/usage/processing-pipelines).
|
|||
|
||||
## Architecture {#architecture}
|
||||
|
||||
import Architecture101 from 'usage/101/\_architecture.mdx'
|
||||
import Architecture101 from 'usage/101/_architecture.mdx'
|
||||
|
||||
<Architecture101 />
|
||||
|
||||
|
|
@ -384,7 +388,7 @@ it.
|
|||
|
||||
## Serialization {#serialization}
|
||||
|
||||
import Serialization101 from 'usage/101/\_serialization.mdx'
|
||||
import Serialization101 from 'usage/101/_serialization.mdx'
|
||||
|
||||
<Serialization101 />
|
||||
|
||||
|
|
@ -397,7 +401,7 @@ guide on [saving and loading](/usage/saving-loading#models).
|
|||
|
||||
## Training {#training}
|
||||
|
||||
import Training101 from 'usage/101/\_training.mdx'
|
||||
import Training101 from 'usage/101/_training.mdx'
|
||||
|
||||
<Training101 />
|
||||
|
||||
|
|
@ -476,7 +480,7 @@ for trainable components.
|
|||
|
||||
## Language data {#language-data}
|
||||
|
||||
import LanguageData101 from 'usage/101/\_language-data.mdx'
|
||||
import LanguageData101 from 'usage/101/_language-data.mdx'
|
||||
|
||||
<LanguageData101 />
|
||||
|
||||
|
|
@ -513,10 +517,11 @@ via the following platforms:
|
|||
questions** and everything related to problems with your specific code. The
|
||||
Stack Overflow community is much larger than ours, so if your problem can be
|
||||
solved by others, you'll receive help much quicker.
|
||||
- [GitHub discussions](https://github.com/explosion/spaCy/discussions): **General
|
||||
discussion**, **project ideas** and **usage questions**. Meet other community
|
||||
members to get help with a specific code implementation, discuss ideas for new
|
||||
projects/plugins, support more languages, and share best practices.
|
||||
- [GitHub discussions](https://github.com/explosion/spaCy/discussions):
|
||||
**General discussion**, **project ideas** and **usage questions**. Meet other
|
||||
community members to get help with a specific code implementation, discuss
|
||||
ideas for new projects/plugins, support more languages, and share best
|
||||
practices.
|
||||
- [GitHub issue tracker](https://github.com/explosion/spaCy/issues): **Bug
|
||||
reports** and **improvement suggestions**, i.e. everything that's likely
|
||||
spaCy's fault. This also includes problems with the trained pipelines beyond
|
||||
|
|
@ -588,7 +593,8 @@ project is using spaCy, you can grab one of our **spaCy badges** here:
|
|||
[](https://spacy.io)
|
||||
```
|
||||
|
||||
<img src={`https://img.shields.io/badge/made%20with%20❤%20and-spaCy-09a3d5.svg`}
|
||||
<img
|
||||
src={`https://img.shields.io/badge/made%20with%20❤%20and-spaCy-09a3d5.svg`}
|
||||
/>
|
||||
|
||||
```markdown
|
||||
|
|
|
|||
|
|
@ -17,7 +17,7 @@ menu:
|
|||
|
||||
## Introduction to training {#basics hidden="true"}
|
||||
|
||||
import Training101 from 'usage/101/\_training.mdx'
|
||||
import Training101 from 'usage/101/_training.mdx'
|
||||
|
||||
<Training101 />
|
||||
|
||||
|
|
|
|||
|
|
@ -180,9 +180,9 @@ entirely **in Markdown**, without having to compromise on easy-to-use custom UI
|
|||
components. We're hoping that the Markdown source will make it even easier to
|
||||
contribute to the documentation. For more details, check out the
|
||||
[styleguide](/styleguide) and
|
||||
[source](https://github.com/explosion/spacy/tree/v2.x/website). While
|
||||
converting the pages to Markdown, we've also fixed a bunch of typos, improved
|
||||
the existing pages and added some new content:
|
||||
[source](https://github.com/explosion/spacy/tree/v2.x/website). While converting
|
||||
the pages to Markdown, we've also fixed a bunch of typos, improved the existing
|
||||
pages and added some new content:
|
||||
|
||||
- **Usage Guide:** [Rule-based Matching](/usage/rule-based-matching)<br/>How to
|
||||
use the `Matcher`, `PhraseMatcher` and the new `EntityRuler`, and write
|
||||
|
|
|
|||
|
|
@ -79,7 +79,11 @@ displacy.serve(doc, style="span", options={"spans_key": "custom"})
|
|||
|
||||
import DisplacySpanHtml from 'images/displacy-span.html'
|
||||
|
||||
<Iframe title="displaCy visualizer for overlapping spans" html={DisplacySpanHtml} height={180} />
|
||||
<Iframe
|
||||
title="displaCy visualizer for overlapping spans"
|
||||
html={DisplacySpanHtml}
|
||||
height={180}
|
||||
/>
|
||||
|
||||
## Additional features and improvements
|
||||
|
||||
|
|
|
|||
|
|
@ -63,8 +63,8 @@ All CNN pipelines have been extended with whitespace augmentation.
|
|||
|
||||
The English CNN pipelines have new word vectors:
|
||||
|
||||
| Package | Model Version | TAG | Parser LAS | NER F |
|
||||
| ----------------------------------------------- | ------------- | ---: | ---------: | ----: |
|
||||
| Package | Model Version | TAG | Parser LAS | NER F |
|
||||
| --------------------------------------------- | ------------- | ---: | ---------: | ----: |
|
||||
| [`en_core_web_md`](/models/en#en_core_web_md) | v3.3.0 | 97.3 | 90.1 | 84.6 |
|
||||
| [`en_core_web_md`](/models/en#en_core_web_md) | v3.4.0 | 97.2 | 90.3 | 85.5 |
|
||||
| [`en_core_web_lg`](/models/en#en_core_web_lg) | v3.3.0 | 97.4 | 90.1 | 85.3 |
|
||||
|
|
|
|||
|
|
@ -88,7 +88,7 @@ giving you access to thousands of pretrained models for your pipelines.
|
|||
|
||||
|
||||
|
||||
import Benchmarks from 'usage/\_benchmarks-models.mdx'
|
||||
import Benchmarks from 'usage/_benchmarks-models.mdx'
|
||||
|
||||
<Benchmarks />
|
||||
|
||||
|
|
|
|||
|
|
@ -118,12 +118,16 @@ displacy.serve(doc, style="ent")
|
|||
|
||||
import DisplacyEntHtml from 'images/displacy-ent2.html'
|
||||
|
||||
<Iframe title="displaCy visualizer for entities" html={DisplacyEntHtml} height={180} />
|
||||
<Iframe
|
||||
title="displaCy visualizer for entities"
|
||||
html={DisplacyEntHtml}
|
||||
height={180}
|
||||
/>
|
||||
|
||||
The entity visualizer lets you customize the following `options`:
|
||||
|
||||
| Argument | Description |
|
||||
| -------- | ------------------------------------------------------------------------------------------------------------- |
|
||||
| -------- | ------------------------------------------------------------------------------------------------------------- | ------ |
|
||||
| `ents` | Entity types to highlight (`None` for all types). Defaults to `None`. ~~Optional[List[str]]~~ | `None` |
|
||||
| `colors` | Color overrides. Entity types should be mapped to color names or values. Defaults to `{}`. ~~Dict[str, str]~~ |
|
||||
|
||||
|
|
@ -145,7 +149,11 @@ use the `colors` setting to add your own colors for them.
|
|||
|
||||
import DisplacyEntCustomHtml from 'images/displacy-ent-custom.html'
|
||||
|
||||
<Iframe title="displaCy visualizer for entities (custom styling)" html={DisplacyEntCustomHtml} height={225} />
|
||||
<Iframe
|
||||
title="displaCy visualizer for entities (custom styling)"
|
||||
html={DisplacyEntCustomHtml}
|
||||
height={225}
|
||||
/>
|
||||
|
||||
The above example uses a little trick: Since the background color values are
|
||||
added as the `background` style attribute, you can use any
|
||||
|
|
@ -184,7 +192,7 @@ nlp = spacy.blank("en")
|
|||
doc = nlp(text)
|
||||
|
||||
doc.spans["sc"] = [
|
||||
Span(doc, 3, 6, "ORG"),
|
||||
Span(doc, 3, 6, "ORG"),
|
||||
Span(doc, 5, 6, "GPE"),
|
||||
]
|
||||
|
||||
|
|
@ -193,8 +201,11 @@ displacy.serve(doc, style="span")
|
|||
|
||||
import DisplacySpanHtml from 'images/displacy-span.html'
|
||||
|
||||
<Iframe title="displaCy visualizer for overlapping spans" html={DisplacySpanHtml} height={180} />
|
||||
|
||||
<Iframe
|
||||
title="displaCy visualizer for overlapping spans"
|
||||
html={DisplacySpanHtml}
|
||||
height={180}
|
||||
/>
|
||||
|
||||
The span visualizer lets you customize the following `options`:
|
||||
|
||||
|
|
@ -205,8 +216,8 @@ The span visualizer lets you customize the following `options`:
|
|||
| `kb_url_template` | Optional template to construct the KB url for the entity to link to. Expects a python f-string format with single field to fill in ~~Optional[str]~~ |
|
||||
| `colors` | Color overrides. Entity types should be mapped to color names or values. ~~Dict[str, str]~~ |
|
||||
|
||||
Because spans can be stored across different keys in `doc.spans`, you need to specify
|
||||
which one displaCy should use with `spans_key` (`sc` is the default).
|
||||
Because spans can be stored across different keys in `doc.spans`, you need to
|
||||
specify which one displaCy should use with `spans_key` (`sc` is the default).
|
||||
|
||||
> #### Options example
|
||||
>
|
||||
|
|
@ -214,12 +225,15 @@ which one displaCy should use with `spans_key` (`sc` is the default).
|
|||
> doc.spans["custom"] = [Span(doc, 3, 6, "BANK")]
|
||||
> options = {"spans_key": "custom"}
|
||||
> displacy.serve(doc, style="span", options=options)
|
||||
> ```
|
||||
|
||||
import DisplacySpanCustomHtml from 'images/displacy-span-custom.html'
|
||||
|
||||
<Iframe title="displaCy visualizer for spans (custom spans_key)" html={DisplacySpanCustomHtml} height={225} />
|
||||
|
||||
|
||||
<Iframe
|
||||
title="displaCy visualizer for spans (custom spans_key)"
|
||||
html={DisplacySpanCustomHtml}
|
||||
height={225}
|
||||
/>
|
||||
|
||||
## Using displaCy in Jupyter notebooks {#jupyter}
|
||||
|
||||
|
|
@ -343,11 +357,11 @@ want to visualize output from other libraries, like [NLTK](http://www.nltk.org)
|
|||
or
|
||||
[SyntaxNet](https://github.com/tensorflow/models/tree/master/research/syntaxnet).
|
||||
If you set `manual=True` on either `render()` or `serve()`, you can pass in data
|
||||
in displaCy's format as a dictionary (instead of `Doc` objects). There are helper
|
||||
functions for converting `Doc` objects to displaCy's format for use with `manual=True`:
|
||||
[`displacy.parse_deps`](/api/top-level#displacy.parse_deps),
|
||||
[`displacy.parse_ents`](/api/top-level#displacy.parse_ents),
|
||||
and [`displacy.parse_spans`](/api/top-level#displacy.parse_spans).
|
||||
in displaCy's format as a dictionary (instead of `Doc` objects). There are
|
||||
helper functions for converting `Doc` objects to displaCy's format for use with
|
||||
`manual=True`: [`displacy.parse_deps`](/api/top-level#displacy.parse_deps),
|
||||
[`displacy.parse_ents`](/api/top-level#displacy.parse_ents), and
|
||||
[`displacy.parse_spans`](/api/top-level#displacy.parse_spans).
|
||||
|
||||
> #### Example with parse function
|
||||
>
|
||||
|
|
@ -366,7 +380,6 @@ and [`displacy.parse_spans`](/api/top-level#displacy.parse_spans).
|
|||
> html = displacy.render(ex, style="ent", manual=True)
|
||||
> ```
|
||||
|
||||
|
||||
```python
|
||||
### DEP input
|
||||
{
|
||||
|
|
|
|||
|
|
@ -101,19 +101,19 @@ exports.createPages = ({ graphql, actions }) => {
|
|||
}
|
||||
}
|
||||
`
|
||||
).then(result => {
|
||||
).then((result) => {
|
||||
if (result.errors) {
|
||||
console.log(result.errors)
|
||||
reject(result.errors)
|
||||
}
|
||||
|
||||
const sectionData = result.data.site.siteMetadata.sections
|
||||
const sections = Object.assign({}, ...sectionData.map(s => ({ [s.id]: s })))
|
||||
const sections = Object.assign({}, ...sectionData.map((s) => ({ [s.id]: s })))
|
||||
|
||||
/* Regular pages */
|
||||
|
||||
const pages = result.data.allFile.edges
|
||||
pages.forEach(page => {
|
||||
pages.forEach((page) => {
|
||||
const { name } = path.parse(page.node.absolutePath)
|
||||
if (!name.startsWith('_')) {
|
||||
const mdx = page.node.childMdx || {}
|
||||
|
|
@ -184,7 +184,7 @@ exports.createPages = ({ graphql, actions }) => {
|
|||
})
|
||||
|
||||
const universe = result.data.site.siteMetadata.universe.resources
|
||||
universe.forEach(page => {
|
||||
universe.forEach((page) => {
|
||||
const slug = `/universe/project/${page.id}`
|
||||
|
||||
createPage({
|
||||
|
|
@ -203,8 +203,11 @@ exports.createPages = ({ graphql, actions }) => {
|
|||
})
|
||||
|
||||
const universeCategories = result.data.site.siteMetadata.universe.categories
|
||||
const categories = [].concat.apply([], universeCategories.map(cat => cat.items))
|
||||
categories.forEach(page => {
|
||||
const categories = [].concat.apply(
|
||||
[],
|
||||
universeCategories.map((cat) => cat.items)
|
||||
)
|
||||
categories.forEach((page) => {
|
||||
const slug = `/universe/category/${page.id}`
|
||||
|
||||
createPage({
|
||||
|
|
|
|||
|
|
@ -36,12 +36,7 @@
|
|||
"name": "Catalan",
|
||||
"example": "Això és una frase.",
|
||||
"has_examples": true,
|
||||
"models": [
|
||||
"ca_core_news_sm",
|
||||
"ca_core_news_md",
|
||||
"ca_core_news_lg",
|
||||
"ca_core_news_trf"
|
||||
]
|
||||
"models": ["ca_core_news_sm", "ca_core_news_md", "ca_core_news_lg", "ca_core_news_trf"]
|
||||
},
|
||||
{
|
||||
"code": "cs",
|
||||
|
|
@ -53,22 +48,12 @@
|
|||
"name": "Danish",
|
||||
"example": "Dette er en sætning.",
|
||||
"has_examples": true,
|
||||
"models": [
|
||||
"da_core_news_sm",
|
||||
"da_core_news_md",
|
||||
"da_core_news_lg",
|
||||
"da_core_news_trf"
|
||||
]
|
||||
"models": ["da_core_news_sm", "da_core_news_md", "da_core_news_lg", "da_core_news_trf"]
|
||||
},
|
||||
{
|
||||
"code": "de",
|
||||
"name": "German",
|
||||
"models": [
|
||||
"de_core_news_sm",
|
||||
"de_core_news_md",
|
||||
"de_core_news_lg",
|
||||
"de_dep_news_trf"
|
||||
],
|
||||
"models": ["de_core_news_sm", "de_core_news_md", "de_core_news_lg", "de_dep_news_trf"],
|
||||
"example": "Dies ist ein Satz.",
|
||||
"has_examples": true
|
||||
},
|
||||
|
|
@ -80,35 +65,21 @@
|
|||
{
|
||||
"code": "el",
|
||||
"name": "Greek",
|
||||
"models": [
|
||||
"el_core_news_sm",
|
||||
"el_core_news_md",
|
||||
"el_core_news_lg"
|
||||
],
|
||||
"models": ["el_core_news_sm", "el_core_news_md", "el_core_news_lg"],
|
||||
"example": "Αυτή είναι μια πρόταση.",
|
||||
"has_examples": true
|
||||
},
|
||||
{
|
||||
"code": "en",
|
||||
"name": "English",
|
||||
"models": [
|
||||
"en_core_web_sm",
|
||||
"en_core_web_md",
|
||||
"en_core_web_lg",
|
||||
"en_core_web_trf"
|
||||
],
|
||||
"models": ["en_core_web_sm", "en_core_web_md", "en_core_web_lg", "en_core_web_trf"],
|
||||
"example": "This is a sentence.",
|
||||
"has_examples": true
|
||||
},
|
||||
{
|
||||
"code": "es",
|
||||
"name": "Spanish",
|
||||
"models": [
|
||||
"es_core_news_sm",
|
||||
"es_core_news_md",
|
||||
"es_core_news_lg",
|
||||
"es_dep_news_trf"
|
||||
],
|
||||
"models": ["es_core_news_sm", "es_core_news_md", "es_core_news_lg", "es_dep_news_trf"],
|
||||
"example": "Esto es una frase.",
|
||||
"has_examples": true
|
||||
},
|
||||
|
|
@ -130,21 +101,12 @@
|
|||
"code": "fi",
|
||||
"name": "Finnish",
|
||||
"has_examples": true,
|
||||
"models": [
|
||||
"fi_core_news_sm",
|
||||
"fi_core_news_md",
|
||||
"fi_core_news_lg"
|
||||
]
|
||||
"models": ["fi_core_news_sm", "fi_core_news_md", "fi_core_news_lg"]
|
||||
},
|
||||
{
|
||||
"code": "fr",
|
||||
"name": "French",
|
||||
"models": [
|
||||
"fr_core_news_sm",
|
||||
"fr_core_news_md",
|
||||
"fr_core_news_lg",
|
||||
"fr_dep_news_trf"
|
||||
],
|
||||
"models": ["fr_core_news_sm", "fr_core_news_md", "fr_core_news_lg", "fr_dep_news_trf"],
|
||||
"example": "C'est une phrase.",
|
||||
"has_examples": true
|
||||
},
|
||||
|
|
@ -178,11 +140,7 @@
|
|||
"code": "hr",
|
||||
"name": "Croatian",
|
||||
"has_examples": true,
|
||||
"models": [
|
||||
"hr_core_news_sm",
|
||||
"hr_core_news_md",
|
||||
"hr_core_news_lg"
|
||||
]
|
||||
"models": ["hr_core_news_sm", "hr_core_news_md", "hr_core_news_lg"]
|
||||
},
|
||||
{
|
||||
"code": "hsb",
|
||||
|
|
@ -213,23 +171,14 @@
|
|||
{
|
||||
"code": "it",
|
||||
"name": "Italian",
|
||||
"models": [
|
||||
"it_core_news_sm",
|
||||
"it_core_news_md",
|
||||
"it_core_news_lg"
|
||||
],
|
||||
"models": ["it_core_news_sm", "it_core_news_md", "it_core_news_lg"],
|
||||
"example": "Questa è una frase.",
|
||||
"has_examples": true
|
||||
},
|
||||
{
|
||||
"code": "ja",
|
||||
"name": "Japanese",
|
||||
"models": [
|
||||
"ja_core_news_sm",
|
||||
"ja_core_news_md",
|
||||
"ja_core_news_lg",
|
||||
"ja_core_news_trf"
|
||||
],
|
||||
"models": ["ja_core_news_sm", "ja_core_news_md", "ja_core_news_lg", "ja_core_news_trf"],
|
||||
"dependencies": [
|
||||
{
|
||||
"name": "SudachiPy",
|
||||
|
|
@ -263,11 +212,7 @@
|
|||
],
|
||||
"example": "이것은 문장입니다.",
|
||||
"has_examples": true,
|
||||
"models": [
|
||||
"ko_core_news_sm",
|
||||
"ko_core_news_md",
|
||||
"ko_core_news_lg"
|
||||
]
|
||||
"models": ["ko_core_news_sm", "ko_core_news_md", "ko_core_news_lg"]
|
||||
},
|
||||
{
|
||||
"code": "ky",
|
||||
|
|
@ -299,11 +244,7 @@
|
|||
"code": "lt",
|
||||
"name": "Lithuanian",
|
||||
"has_examples": true,
|
||||
"models": [
|
||||
"lt_core_news_sm",
|
||||
"lt_core_news_md",
|
||||
"lt_core_news_lg"
|
||||
]
|
||||
"models": ["lt_core_news_sm", "lt_core_news_md", "lt_core_news_lg"]
|
||||
},
|
||||
{
|
||||
"code": "lv",
|
||||
|
|
@ -312,11 +253,7 @@
|
|||
{
|
||||
"code": "mk",
|
||||
"name": "Macedonian",
|
||||
"models": [
|
||||
"mk_core_news_sm",
|
||||
"mk_core_news_md",
|
||||
"mk_core_news_lg"
|
||||
]
|
||||
"models": ["mk_core_news_sm", "mk_core_news_md", "mk_core_news_lg"]
|
||||
},
|
||||
{
|
||||
"code": "ml",
|
||||
|
|
@ -332,11 +269,7 @@
|
|||
"name": "Norwegian Bokmål",
|
||||
"example": "Dette er en setning.",
|
||||
"has_examples": true,
|
||||
"models": [
|
||||
"nb_core_news_sm",
|
||||
"nb_core_news_md",
|
||||
"nb_core_news_lg"
|
||||
]
|
||||
"models": ["nb_core_news_sm", "nb_core_news_md", "nb_core_news_lg"]
|
||||
},
|
||||
{
|
||||
"code": "ne",
|
||||
|
|
@ -346,11 +279,7 @@
|
|||
{
|
||||
"code": "nl",
|
||||
"name": "Dutch",
|
||||
"models": [
|
||||
"nl_core_news_sm",
|
||||
"nl_core_news_md",
|
||||
"nl_core_news_lg"
|
||||
],
|
||||
"models": ["nl_core_news_sm", "nl_core_news_md", "nl_core_news_lg"],
|
||||
"example": "Dit is een zin.",
|
||||
"has_examples": true
|
||||
},
|
||||
|
|
@ -359,20 +288,12 @@
|
|||
"name": "Polish",
|
||||
"example": "To jest zdanie.",
|
||||
"has_examples": true,
|
||||
"models": [
|
||||
"pl_core_news_sm",
|
||||
"pl_core_news_md",
|
||||
"pl_core_news_lg"
|
||||
]
|
||||
"models": ["pl_core_news_sm", "pl_core_news_md", "pl_core_news_lg"]
|
||||
},
|
||||
{
|
||||
"code": "pt",
|
||||
"name": "Portuguese",
|
||||
"models": [
|
||||
"pt_core_news_sm",
|
||||
"pt_core_news_md",
|
||||
"pt_core_news_lg"
|
||||
],
|
||||
"models": ["pt_core_news_sm", "pt_core_news_md", "pt_core_news_lg"],
|
||||
"example": "Esta é uma frase.",
|
||||
"has_examples": true
|
||||
},
|
||||
|
|
@ -381,11 +302,7 @@
|
|||
"name": "Romanian",
|
||||
"example": "Aceasta este o propoziție.",
|
||||
"has_examples": true,
|
||||
"models": [
|
||||
"ro_core_news_sm",
|
||||
"ro_core_news_md",
|
||||
"ro_core_news_lg"
|
||||
]
|
||||
"models": ["ro_core_news_sm", "ro_core_news_md", "ro_core_news_lg"]
|
||||
},
|
||||
{
|
||||
"code": "ru",
|
||||
|
|
@ -397,11 +314,7 @@
|
|||
"url": "https://github.com/no-plagiarism/pymorphy3"
|
||||
}
|
||||
],
|
||||
"models": [
|
||||
"ru_core_news_sm",
|
||||
"ru_core_news_md",
|
||||
"ru_core_news_lg"
|
||||
]
|
||||
"models": ["ru_core_news_sm", "ru_core_news_md", "ru_core_news_lg"]
|
||||
},
|
||||
{
|
||||
"code": "sa",
|
||||
|
|
@ -438,11 +351,7 @@
|
|||
"code": "sv",
|
||||
"name": "Swedish",
|
||||
"has_examples": true,
|
||||
"models": [
|
||||
"sv_core_news_sm",
|
||||
"sv_core_news_md",
|
||||
"sv_core_news_lg"
|
||||
]
|
||||
"models": ["sv_core_news_sm", "sv_core_news_md", "sv_core_news_lg"]
|
||||
},
|
||||
{
|
||||
"code": "ta",
|
||||
|
|
@ -496,12 +405,7 @@
|
|||
"code": "uk",
|
||||
"name": "Ukrainian",
|
||||
"has_examples": true,
|
||||
"models": [
|
||||
"uk_core_news_sm",
|
||||
"uk_core_news_md",
|
||||
"uk_core_news_lg",
|
||||
"uk_core_news_trf"
|
||||
],
|
||||
"models": ["uk_core_news_sm", "uk_core_news_md", "uk_core_news_lg", "uk_core_news_trf"],
|
||||
"dependencies": [
|
||||
{
|
||||
"name": "pymorphy3",
|
||||
|
|
@ -532,10 +436,7 @@
|
|||
{
|
||||
"code": "xx",
|
||||
"name": "Multi-language",
|
||||
"models": [
|
||||
"xx_ent_wiki_sm",
|
||||
"xx_sent_ud_sm"
|
||||
],
|
||||
"models": ["xx_ent_wiki_sm", "xx_sent_ud_sm"],
|
||||
"example": "This is a sentence about Facebook."
|
||||
},
|
||||
{
|
||||
|
|
@ -546,12 +447,7 @@
|
|||
{
|
||||
"code": "zh",
|
||||
"name": "Chinese",
|
||||
"models": [
|
||||
"zh_core_web_sm",
|
||||
"zh_core_web_md",
|
||||
"zh_core_web_lg",
|
||||
"zh_core_web_trf"
|
||||
],
|
||||
"models": ["zh_core_web_sm", "zh_core_web_md", "zh_core_web_lg", "zh_core_web_trf"],
|
||||
"dependencies": [
|
||||
{
|
||||
"name": "Jieba",
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
{
|
||||
"resources": [
|
||||
{
|
||||
{
|
||||
"id": "grecy",
|
||||
"title": "greCy",
|
||||
"slogan": "Ancient Greek pipelines for spaCy",
|
||||
|
|
@ -60,12 +60,8 @@
|
|||
"github": "Ce11an",
|
||||
"website": "https://www.linkedin.com/in/cellan-hall/"
|
||||
},
|
||||
"category": [
|
||||
"extension"
|
||||
],
|
||||
"tags": [
|
||||
"text-processing"
|
||||
]
|
||||
"category": ["extension"],
|
||||
"tags": ["text-processing"]
|
||||
},
|
||||
{
|
||||
"id": "Zshot",
|
||||
|
|
@ -195,9 +191,7 @@
|
|||
"description": "Aim-spaCy helps to easily collect, store and explore training logs for spaCy, including: hyper-parameters, metrics and displaCy visualizations",
|
||||
"github": "aimhubio/aim-spacy",
|
||||
"pip": "aim-spacy",
|
||||
"code_example": [
|
||||
"https://github.com/aimhubio/aim-spacy/tree/master/examples"
|
||||
],
|
||||
"code_example": ["https://github.com/aimhubio/aim-spacy/tree/master/examples"],
|
||||
"code_language": "python",
|
||||
"url": "https://aimstack.io/spacy",
|
||||
"thumb": "https://user-images.githubusercontent.com/13848158/172912427-ee9327ea-3cd8-47fa-8427-6c0d36cd831f.png",
|
||||
|
|
@ -266,7 +260,7 @@
|
|||
"code_language": "python",
|
||||
"author": "Peter Baumgartner",
|
||||
"author_links": {
|
||||
"twitter" : "pmbaumgartner",
|
||||
"twitter": "pmbaumgartner",
|
||||
"github": "pmbaumgartner",
|
||||
"website": "https://www.peterbaumgartner.com/"
|
||||
},
|
||||
|
|
@ -286,7 +280,7 @@
|
|||
"code_language": "python",
|
||||
"author": "Explosion",
|
||||
"author_links": {
|
||||
"twitter" : "explosion_ai",
|
||||
"twitter": "explosion_ai",
|
||||
"github": "explosion",
|
||||
"website": "https://explosion.ai/"
|
||||
},
|
||||
|
|
@ -748,7 +742,7 @@
|
|||
"code_language": "python",
|
||||
"author": "Keith Rozario",
|
||||
"author_links": {
|
||||
"twitter" : "keithrozario",
|
||||
"twitter": "keithrozario",
|
||||
"github": "keithrozario",
|
||||
"website": "https://www.keithrozario.com"
|
||||
},
|
||||
|
|
@ -2664,10 +2658,7 @@
|
|||
"github": "davidberenstein1957",
|
||||
"website": "https://www.linkedin.com/in/david-berenstein-1bab11105/"
|
||||
},
|
||||
"category": [
|
||||
"pipeline",
|
||||
"standalone"
|
||||
],
|
||||
"category": ["pipeline", "standalone"],
|
||||
"tags": [
|
||||
"classification",
|
||||
"zero-shot",
|
||||
|
|
@ -2720,14 +2711,8 @@
|
|||
"github": "davidberenstein1957",
|
||||
"website": "https://www.linkedin.com/in/david-berenstein-1bab11105/"
|
||||
},
|
||||
"category": [
|
||||
"pipeline"
|
||||
],
|
||||
"tags": [
|
||||
"ner",
|
||||
"few-shot",
|
||||
"gensim"
|
||||
],
|
||||
"category": ["pipeline"],
|
||||
"tags": ["ner", "few-shot", "gensim"],
|
||||
"spacy_version": 3
|
||||
},
|
||||
{
|
||||
|
|
@ -2778,16 +2763,8 @@
|
|||
"github": "davidberenstein1957",
|
||||
"website": "https://www.linkedin.com/in/david-berenstein-1bab11105/"
|
||||
},
|
||||
"category": [
|
||||
"pipeline",
|
||||
"standalone"
|
||||
],
|
||||
"tags": [
|
||||
"coreference",
|
||||
"multi-lingual",
|
||||
"cross-lingual",
|
||||
"allennlp"
|
||||
],
|
||||
"category": ["pipeline", "standalone"],
|
||||
"tags": ["coreference", "multi-lingual", "cross-lingual", "allennlp"],
|
||||
"spacy_version": 3
|
||||
},
|
||||
{
|
||||
|
|
@ -2952,7 +2929,7 @@
|
|||
"description": "Collection of NLP visualizations for NER and syntax tree markup. Similar to [displaCy](https://explosion.ai/demos/displacy) and [displaCy ENT](https://explosion.ai/demos/displacy-ent).",
|
||||
"github": "natasha/ipymarkup",
|
||||
"image": "https://github.com/natasha/ipymarkup/blob/master/table.png?raw=true",
|
||||
"pip":"pip install ipymarkup",
|
||||
"pip": "pip install ipymarkup",
|
||||
"code_example": [
|
||||
"from ipymarkup import show_span_ascii_markup, show_dep_ascii_markup",
|
||||
"",
|
||||
|
|
@ -3715,7 +3692,15 @@
|
|||
"website": "https://brucewlee.github.io/"
|
||||
},
|
||||
"category": ["research", "scientific"],
|
||||
"tags": ["Readability", "Simplification", "Feature Extraction", "Syntax", "Discourse", "Semantics", "Lexical"]
|
||||
"tags": [
|
||||
"Readability",
|
||||
"Simplification",
|
||||
"Feature Extraction",
|
||||
"Syntax",
|
||||
"Discourse",
|
||||
"Semantics",
|
||||
"Lexical"
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": "hmrb",
|
||||
|
|
@ -4063,7 +4048,6 @@
|
|||
"github": "yasufumy"
|
||||
}
|
||||
}
|
||||
|
||||
],
|
||||
|
||||
"categories": [
|
||||
|
|
|
|||
|
|
@ -34,7 +34,7 @@ export default function Accordion({ title, id, expanded = false, spaced = false,
|
|||
to={`#${id}`}
|
||||
className={classes.anchor}
|
||||
hidden
|
||||
onClick={event => event.stopPropagation()}
|
||||
onClick={(event) => event.stopPropagation()}
|
||||
>
|
||||
¶
|
||||
</Link>
|
||||
|
|
|
|||
|
|
@ -16,13 +16,13 @@ import classes from '../styles/code.module.sass'
|
|||
const WRAP_THRESHOLD = 30
|
||||
const CLI_GROUPS = ['init', 'debug', 'project', 'ray', 'huggingface-hub']
|
||||
|
||||
export default props => (
|
||||
export default (props) => (
|
||||
<Pre>
|
||||
<Code {...props} />
|
||||
</Pre>
|
||||
)
|
||||
|
||||
export const Pre = props => {
|
||||
export const Pre = (props) => {
|
||||
return <pre className={classes.pre}>{props.children}</pre>
|
||||
}
|
||||
|
||||
|
|
@ -100,7 +100,7 @@ function replacePrompt(line, prompt, isFirst = false) {
|
|||
}
|
||||
|
||||
function parseArgs(raw) {
|
||||
let args = raw.split(' ').filter(arg => arg)
|
||||
let args = raw.split(' ').filter((arg) => arg)
|
||||
const result = {}
|
||||
while (args.length) {
|
||||
let opt = args.shift()
|
||||
|
|
@ -167,7 +167,7 @@ function formatCode(html, lang, prompt) {
|
|||
const lines = html
|
||||
.trim()
|
||||
.split('\n')
|
||||
.map(line =>
|
||||
.map((line) =>
|
||||
line
|
||||
.split(' | ')
|
||||
.map((l, i) => convertLine(l, i))
|
||||
|
|
@ -233,17 +233,8 @@ export class Code extends React.Component {
|
|||
}
|
||||
|
||||
render() {
|
||||
const {
|
||||
lang,
|
||||
title,
|
||||
executable,
|
||||
github,
|
||||
prompt,
|
||||
wrap,
|
||||
highlight,
|
||||
className,
|
||||
children,
|
||||
} = this.props
|
||||
const { lang, title, executable, github, prompt, wrap, highlight, className, children } =
|
||||
this.props
|
||||
const codeClassNames = classNames(classes.code, className, `language-${lang}`, {
|
||||
[classes.wrap]: !!highlight || !!wrap || lang === 'cli',
|
||||
[classes.cli]: lang === 'cli',
|
||||
|
|
@ -263,7 +254,7 @@ export class Code extends React.Component {
|
|||
}
|
||||
|
||||
const codeText = Array.isArray(children) ? children.join('') : children || ''
|
||||
const highlightRange = highlight ? rangeParser.parse(highlight).filter(n => n > 0) : []
|
||||
const highlightRange = highlight ? rangeParser.parse(highlight).filter((n) => n > 0) : []
|
||||
const rawHtml = ['none', 'cli'].includes(lang)
|
||||
? codeText
|
||||
: highlightCode(lang, codeText, highlightRange)
|
||||
|
|
@ -280,7 +271,7 @@ export class Code extends React.Component {
|
|||
const JuniperWrapper = ({ Juniper, title, lang, children }) => (
|
||||
<StaticQuery
|
||||
query={query}
|
||||
render={data => {
|
||||
render={(data) => {
|
||||
const { binderUrl, binderBranch, binderVersion } = data.site.siteMetadata
|
||||
const juniperTitle = title || 'Editable Code'
|
||||
return (
|
||||
|
|
|
|||
|
|
@ -13,7 +13,7 @@ export default function Footer({ wide = false }) {
|
|||
return (
|
||||
<StaticQuery
|
||||
query={query}
|
||||
render={data => {
|
||||
render={(data) => {
|
||||
const { companyUrl, company, footer, newsletter } = data.site.siteMetadata
|
||||
return (
|
||||
<footer className={classes.root}>
|
||||
|
|
|
|||
|
|
@ -27,11 +27,11 @@ const GitHubCode = ({ url, lang, errorMsg = defaultErrorMsg, className }) => {
|
|||
if (!initialized) {
|
||||
setCode(null)
|
||||
fetch(rawUrl)
|
||||
.then(res => res.text().then(text => ({ text, ok: res.ok })))
|
||||
.then((res) => res.text().then((text) => ({ text, ok: res.ok })))
|
||||
.then(({ text, ok }) => {
|
||||
setCode(ok ? text : errorMsg)
|
||||
})
|
||||
.catch(err => {
|
||||
.catch((err) => {
|
||||
setCode(errorMsg)
|
||||
console.error(err)
|
||||
})
|
||||
|
|
|
|||
|
|
@ -14,7 +14,7 @@ export default class Juniper extends React.Component {
|
|||
state = { kernel: null, renderers: null, fromStorage: null }
|
||||
|
||||
componentDidMount() {
|
||||
const renderers = standardRendererFactories.filter(factory =>
|
||||
const renderers = standardRendererFactories.filter((factory) =>
|
||||
factory.mimeTypes.includes('text/latex') ? window.MathJax : true
|
||||
)
|
||||
|
||||
|
|
@ -52,7 +52,7 @@ export default class Juniper extends React.Component {
|
|||
this.log(() => console.info('building', { binderUrl }))
|
||||
return new Promise((resolve, reject) => {
|
||||
const es = new EventSource(binderUrl)
|
||||
es.onerror = err => {
|
||||
es.onerror = (err) => {
|
||||
es.close()
|
||||
this.log(() => console.error('failed'))
|
||||
reject(new Error(err))
|
||||
|
|
@ -92,7 +92,7 @@ export default class Juniper extends React.Component {
|
|||
window.localStorage.setItem(this.props.storageKey, json)
|
||||
}
|
||||
const serverSettings = ServerConnection.makeSettings(settings)
|
||||
return Kernel.startNew({ type: this.props.kernelType, serverSettings }).then(kernel => {
|
||||
return Kernel.startNew({ type: this.props.kernelType, serverSettings }).then((kernel) => {
|
||||
this.log(() => console.info('ready'))
|
||||
return kernel
|
||||
})
|
||||
|
|
@ -116,7 +116,7 @@ export default class Juniper extends React.Component {
|
|||
}
|
||||
if (this.props.useBinder) {
|
||||
return this.requestBinder(this.props.repo, this.props.branch, this.props.url).then(
|
||||
settings => this.requestKernel(settings)
|
||||
(settings) => this.requestKernel(settings)
|
||||
)
|
||||
}
|
||||
return this.requestKernel(this.props.serverSettings)
|
||||
|
|
@ -173,12 +173,8 @@ export default class Juniper extends React.Component {
|
|||
name: 'stdout',
|
||||
text: `${action} Docker container on ${url}...`,
|
||||
})
|
||||
new Promise((resolve, reject) =>
|
||||
this.getKernel()
|
||||
.then(resolve)
|
||||
.catch(reject)
|
||||
)
|
||||
.then(kernel => {
|
||||
new Promise((resolve, reject) => this.getKernel().then(resolve).catch(reject))
|
||||
.then((kernel) => {
|
||||
this.setState({ kernel })
|
||||
this.renderResponse(outputArea, code)
|
||||
})
|
||||
|
|
@ -203,7 +199,7 @@ export default class Juniper extends React.Component {
|
|||
<div className={this.props.classNames.cell}>
|
||||
<div
|
||||
className={this.props.classNames.input}
|
||||
ref={x => {
|
||||
ref={(x) => {
|
||||
this.inputRef = x
|
||||
}}
|
||||
/>
|
||||
|
|
@ -211,7 +207,7 @@ export default class Juniper extends React.Component {
|
|||
{this.props.msgButton}
|
||||
</button>
|
||||
<div
|
||||
ref={x => {
|
||||
ref={(x) => {
|
||||
this.outputRef = x
|
||||
}}
|
||||
className={this.props.classNames.output}
|
||||
|
|
|
|||
|
|
@ -7,7 +7,8 @@ import Icon from './icon'
|
|||
import classes from '../styles/link.module.sass'
|
||||
import { isString, isImage } from './util'
|
||||
|
||||
const internalRegex = /(http(s?)):\/\/(prodi.gy|spacy.io|irl.spacy.io|explosion.ai|course.spacy.io)/gi
|
||||
const internalRegex =
|
||||
/(http(s?)):\/\/(prodi.gy|spacy.io|irl.spacy.io|explosion.ai|course.spacy.io)/gi
|
||||
|
||||
const Whitespace = ({ children }) => (
|
||||
// Ensure that links are always wrapped in spaces
|
||||
|
|
|
|||
|
|
@ -4,8 +4,8 @@ import classNames from 'classnames'
|
|||
import classes from '../styles/list.module.sass'
|
||||
import { replaceEmoji } from './icon'
|
||||
|
||||
export const Ol = props => <ol className={classes.ol} {...props} />
|
||||
export const Ul = props => <ul className={classes.ul} {...props} />
|
||||
export const Ol = (props) => <ol className={classes.ol} {...props} />
|
||||
export const Ul = (props) => <ul className={classes.ul} {...props} />
|
||||
export const Li = ({ children, emoji, ...props }) => {
|
||||
const { hasIcon, content } = replaceEmoji(children)
|
||||
const liClassNames = classNames(classes.li, {
|
||||
|
|
|
|||
|
|
@ -11,7 +11,7 @@ import classes from '../styles/quickstart.module.sass'
|
|||
|
||||
function getNewChecked(optionId, checkedForId, multiple) {
|
||||
if (!multiple) return [optionId]
|
||||
if (checkedForId.includes(optionId)) return checkedForId.filter(opt => opt !== optionId)
|
||||
if (checkedForId.includes(optionId)) return checkedForId.filter((opt) => opt !== optionId)
|
||||
return [...checkedForId, optionId]
|
||||
}
|
||||
|
||||
|
|
@ -42,12 +42,12 @@ const Quickstart = ({
|
|||
const [copySuccess, setCopySuccess] = useState(false)
|
||||
const [otherState, setOtherState] = useState({})
|
||||
const setOther = (id, value) => setOtherState({ ...otherState, [id]: value })
|
||||
const getRawContent = ref => {
|
||||
const getRawContent = (ref) => {
|
||||
if (rawContent !== null) return rawContent
|
||||
if (ref.current && ref.current.childNodes) {
|
||||
// Select all currently visible nodes (spans and text nodes)
|
||||
const result = [...ref.current.childNodes].filter(el => el.offsetParent !== null)
|
||||
return result.map(el => el.textContent).join('\n')
|
||||
const result = [...ref.current.childNodes].filter((el) => el.offsetParent !== null)
|
||||
return result.map((el) => el.textContent).join('\n')
|
||||
}
|
||||
return ''
|
||||
}
|
||||
|
|
@ -60,7 +60,7 @@ const Quickstart = ({
|
|||
const getCss = (id, checkedOptions) => {
|
||||
const checkedForId = checkedOptions[id] || []
|
||||
const exclude = checkedForId
|
||||
.map(value => `:not([data-quickstart-${id}="${value}"])`)
|
||||
.map((value) => `:not([data-quickstart-${id}="${value}"])`)
|
||||
.join('')
|
||||
return `[data-quickstart-results]>[data-quickstart-${id}]${exclude} {display: none}`
|
||||
}
|
||||
|
|
@ -71,7 +71,7 @@ const Quickstart = ({
|
|||
const initialChecked = Object.assign(
|
||||
{},
|
||||
...data.map(({ id, options = [] }) => ({
|
||||
[id]: options.filter(option => option.checked).map(({ id }) => id),
|
||||
[id]: options.filter((option) => option.checked).map(({ id }) => id),
|
||||
}))
|
||||
)
|
||||
const initialStyles = Object.assign(
|
||||
|
|
@ -127,7 +127,7 @@ const Quickstart = ({
|
|||
)}
|
||||
</div>
|
||||
<div className={classes.fields}>
|
||||
{options.map(option => {
|
||||
{options.map((option) => {
|
||||
const optionType = multiple ? 'checkbox' : 'radio'
|
||||
const checkedForId = checked[id] || []
|
||||
return (
|
||||
|
|
@ -298,7 +298,7 @@ const QS = ({ children, prompt = 'bash', divider = false, comment = false, ...pr
|
|||
})
|
||||
const attrs = Object.assign(
|
||||
{},
|
||||
...Object.keys(props).map(key => ({
|
||||
...Object.keys(props).map((key) => ({
|
||||
[`data-quickstart-${key}`]: props[key],
|
||||
}))
|
||||
)
|
||||
|
|
|
|||
|
|
@ -41,7 +41,7 @@ export default function SEO({
|
|||
return (
|
||||
<StaticQuery
|
||||
query={query}
|
||||
render={data => {
|
||||
render={(data) => {
|
||||
const siteMetadata = data.site.siteMetadata
|
||||
const metaDescription = description || siteMetadata.description
|
||||
const pageTitle = getPageTitle(
|
||||
|
|
|
|||
|
|
@ -87,7 +87,7 @@ export default function Sidebar({ items = [], pageMenu = [], slug }) {
|
|||
</Link>
|
||||
{active && !!currentMenu.length && (
|
||||
<ul className={classes.crumbs}>
|
||||
{currentMenu.map(crumb => {
|
||||
{currentMenu.map((crumb) => {
|
||||
const currentActive = activeSection || currentMenu[0].id
|
||||
const crumbClassNames = classNames(classes.crumb, {
|
||||
[classes.crumbActive]: currentActive === crumb.id,
|
||||
|
|
|
|||
|
|
@ -36,7 +36,7 @@ export default function Title({
|
|||
children,
|
||||
...props
|
||||
}) {
|
||||
const hasApiDetails = Object.values(apiDetails || {}).some(v => v)
|
||||
const hasApiDetails = Object.values(apiDetails || {}).some((v) => v)
|
||||
const metaIconProps = { className: classes.metaIcon, width: 18 }
|
||||
return (
|
||||
<header className={classes.root}>
|
||||
|
|
|
|||
|
|
@ -105,7 +105,7 @@ const Headline = ({
|
|||
const headingClassNames = classNames(classes.heading, className, {
|
||||
[classes.clear]: hasAction,
|
||||
})
|
||||
const tags = tag ? tag.split(',').map(t => t.trim()) : []
|
||||
const tags = tag ? tag.split(',').map((t) => t.trim()) : []
|
||||
return (
|
||||
<Component id={id} name={name} className={headingClassNames}>
|
||||
<Permalink id={permalink ? id : null}>{children} </Permalink>
|
||||
|
|
|
|||
|
|
@ -85,9 +85,7 @@ export function htmlToReact(html) {
|
|||
* @returns {Node} - The converted React elements.
|
||||
*/
|
||||
export function markdownToReact(markdown, remarkReactComponents = {}) {
|
||||
return remark()
|
||||
.use(remark2react, { remarkReactComponents })
|
||||
.processSync(markdown).contents
|
||||
return remark().use(remark2react, { remarkReactComponents }).processSync(markdown).contents
|
||||
}
|
||||
|
||||
/**
|
||||
|
|
@ -113,7 +111,7 @@ export function join(arr, delimiter = ', ') {
|
|||
* @return {Object} - The converted object.
|
||||
*/
|
||||
export function arrayToObj(arr, key) {
|
||||
return Object.assign({}, ...arr.map(item => ({ [item[key]]: item })))
|
||||
return Object.assign({}, ...arr.map((item) => ({ [item[key]]: item })))
|
||||
}
|
||||
|
||||
/**
|
||||
|
|
|
|||
|
|
@ -19,7 +19,7 @@ function remarkCodeBlocks(userOptions = {}) {
|
|||
const options = Object.assign({}, defaultOptions, userOptions)
|
||||
|
||||
function transformer(tree) {
|
||||
visit(tree, 'code', node => {
|
||||
visit(tree, 'code', (node) => {
|
||||
if (node.value) {
|
||||
const langName = node.lang || 'none'
|
||||
const lang = options.languageAliases[langName] || langName
|
||||
|
|
|
|||
|
|
@ -17,7 +17,7 @@ const defaultOptions = {
|
|||
function remarkCustomAttrs(userOptions = {}) {
|
||||
const options = Object.assign({}, defaultOptions, userOptions)
|
||||
function transformer(tree) {
|
||||
visit(tree, null, node => {
|
||||
visit(tree, null, (node) => {
|
||||
if (options.elements.includes(node.type)) {
|
||||
if (
|
||||
node.children &&
|
||||
|
|
@ -25,10 +25,13 @@ function remarkCustomAttrs(userOptions = {}) {
|
|||
node.children[0].type === 'text' &&
|
||||
node.children[0].value
|
||||
) {
|
||||
if (node.children.length > 1 && node.children.every(el => el.type === 'text')) {
|
||||
if (
|
||||
node.children.length > 1 &&
|
||||
node.children.every((el) => el.type === 'text')
|
||||
) {
|
||||
// If headlines contain escaped characters, e.g.
|
||||
// Doc.\_\_init\_\_, it will be split into several nodes
|
||||
const mergedText = node.children.map(el => el.value).join('')
|
||||
const mergedText = node.children.map((el) => el.value).join('')
|
||||
node.children[0].value = mergedText
|
||||
node.children = [node.children[0]]
|
||||
}
|
||||
|
|
|
|||
|
|
@ -28,7 +28,7 @@ function remarkWrapSection(userOptions = {}) {
|
|||
const headingsMap = []
|
||||
const newTree = []
|
||||
|
||||
visit(tree, 'import', node => {
|
||||
visit(tree, 'import', (node) => {
|
||||
// For compatibility with MDX / gatsby-mdx, make sure import nodes
|
||||
// are not moved further down into children (which means they're not
|
||||
// recognized and interpreted anymore). Add them to the very start
|
||||
|
|
@ -52,7 +52,7 @@ function remarkWrapSection(userOptions = {}) {
|
|||
index === headingsMap.length ? tree.children.length : headingsMap[index].index
|
||||
const children = tree.children
|
||||
.slice(sectionStartIndex, sectionEndIndex)
|
||||
.filter(node => node.type !== 'import')
|
||||
.filter((node) => node.type !== 'import')
|
||||
|
||||
if (children.length) {
|
||||
const headingId = index === 0 ? 0 : headingsMap[index - 1].id
|
||||
|
|
|
|||
|
|
@ -36,18 +36,18 @@ const Docs = ({ pageContext, children }) => (
|
|||
const isModels = section === 'models'
|
||||
const sidebar = pageContext.sidebar
|
||||
? { items: pageContext.sidebar }
|
||||
: sidebars.find(bar => bar.section === section)
|
||||
: sidebars.find((bar) => bar.section === section)
|
||||
let pageMenu = menu ? menu.map(([text, id]) => ({ text, id })) : []
|
||||
|
||||
if (isModels) {
|
||||
sidebar.items[1].items = languages
|
||||
.filter(({ models }) => models && models.length)
|
||||
.sort((a, b) => a.name.localeCompare(b.name))
|
||||
.map(lang => ({
|
||||
.map((lang) => ({
|
||||
text: lang.name,
|
||||
url: `/models/${lang.code}`,
|
||||
isActive: id === lang.code,
|
||||
menu: lang.models.map(model => ({
|
||||
menu: lang.models.map((model) => ({
|
||||
text: model,
|
||||
id: model,
|
||||
})),
|
||||
|
|
|
|||
|
|
@ -221,7 +221,7 @@ class Layout extends React.Component {
|
|||
export default withMDXScope(Layout)
|
||||
|
||||
export const pageQuery = graphql`
|
||||
query($slug: String!) {
|
||||
query ($slug: String!) {
|
||||
site {
|
||||
siteMetadata {
|
||||
nightly
|
||||
|
|
|
|||
|
|
@ -12,7 +12,7 @@ const WrappedComponent = React.memo(({ scope = {}, components = {}, children, ..
|
|||
if (!children) return null
|
||||
const fullScope = { React, MDXTag, ...scope }
|
||||
const keys = Object.keys(fullScope)
|
||||
const values = keys.map(key => fullScope[key])
|
||||
const values = keys.map((key) => fullScope[key])
|
||||
const fn = new Function('_fn', ...keys, `${children}`) // eslint-disable-line no-new-func
|
||||
const End = fn({}, ...values)
|
||||
return React.createElement(End, { components, ...props })
|
||||
|
|
|
|||
|
|
@ -70,8 +70,7 @@ const MODEL_META = {
|
|||
pipeline: 'Active processing pipeline components in order',
|
||||
components: 'All processing pipeline components (including disabled components)',
|
||||
sources: 'Sources of training data',
|
||||
vecs:
|
||||
'Word vectors included in the package. Packages that only support context vectors compute similarity via the tensors shared with the pipeline.',
|
||||
vecs: 'Word vectors included in the package. Packages that only support context vectors compute similarity via the tensors shared with the pipeline.',
|
||||
benchmark_parser: 'Syntax accuracy',
|
||||
benchmark_ner: 'NER accuracy',
|
||||
benchmark_speed: 'Speed',
|
||||
|
|
@ -113,7 +112,7 @@ function getLatestVersion(modelId, compatibility, prereleases) {
|
|||
|
||||
function formatVectors(data) {
|
||||
if (!data) return 'n/a'
|
||||
if (Object.values(data).every(n => n === 0)) return 'context vectors only'
|
||||
if (Object.values(data).every((n) => n === 0)) return 'context vectors only'
|
||||
const { keys, vectors, width } = data
|
||||
if (keys >= 0) {
|
||||
return `${abbrNum(keys)} keys, ${abbrNum(vectors)} unique vectors (${width} dimensions)`
|
||||
|
|
@ -123,10 +122,10 @@ function formatVectors(data) {
|
|||
}
|
||||
|
||||
function formatAccuracy(data, lang) {
|
||||
const exclude = (lang !== "ja") ? ['speed'] : ['speed', 'morph_acc']
|
||||
const exclude = lang !== 'ja' ? ['speed'] : ['speed', 'morph_acc']
|
||||
if (!data) return []
|
||||
return Object.keys(data)
|
||||
.map(label => {
|
||||
.map((label) => {
|
||||
const value = data[label]
|
||||
return isNaN(value) || exclude.includes(label)
|
||||
? null
|
||||
|
|
@ -136,14 +135,18 @@ function formatAccuracy(data, lang) {
|
|||
help: MODEL_META[label],
|
||||
}
|
||||
})
|
||||
.filter(item => item)
|
||||
.filter((item) => item)
|
||||
}
|
||||
|
||||
function formatDownloadLink(lang, name, version) {
|
||||
const fullName = `${lang}_${name}-${version}`
|
||||
const filename = `${fullName}-py3-none-any.whl`
|
||||
const url = `https://github.com/explosion/spacy-models/releases/download/${fullName}/${filename}`
|
||||
return <Link to={url} hideIcon>{filename}</Link>
|
||||
const fullName = `${lang}_${name}-${version}`
|
||||
const filename = `${fullName}-py3-none-any.whl`
|
||||
const url = `https://github.com/explosion/spacy-models/releases/download/${fullName}/${filename}`
|
||||
return (
|
||||
<Link to={url} hideIcon>
|
||||
{filename}
|
||||
</Link>
|
||||
)
|
||||
}
|
||||
|
||||
function formatModelMeta(data) {
|
||||
|
|
@ -167,7 +170,7 @@ function formatModelMeta(data) {
|
|||
}
|
||||
|
||||
function formatSources(data = []) {
|
||||
const sources = data.map(s => (isString(s) ? { name: s } : s))
|
||||
const sources = data.map((s) => (isString(s) ? { name: s } : s))
|
||||
return sources.map(({ name, url, author }, i) => (
|
||||
<Fragment key={i}>
|
||||
{i > 0 && <br />}
|
||||
|
|
@ -179,7 +182,7 @@ function formatSources(data = []) {
|
|||
|
||||
function linkComponents(components = []) {
|
||||
return join(
|
||||
components.map(c => (
|
||||
components.map((c) => (
|
||||
<Fragment key={c}>
|
||||
<OptionalLink to={COMPONENT_LINKS[c]} hideIcon>
|
||||
<InlineCode>{c}</InlineCode>
|
||||
|
|
@ -210,23 +213,23 @@ const Model = ({
|
|||
const [isError, setIsError] = useState(true)
|
||||
const [meta, setMeta] = useState({})
|
||||
const { type, genre, size } = getModelComponents(name)
|
||||
const display_type = type === 'core' && (size === 'sm' || size === 'trf') ? 'core_no_vectors' : type
|
||||
const version = useMemo(() => getLatestVersion(name, compatibility, prereleases), [
|
||||
name,
|
||||
compatibility,
|
||||
prereleases,
|
||||
])
|
||||
const display_type =
|
||||
type === 'core' && (size === 'sm' || size === 'trf') ? 'core_no_vectors' : type
|
||||
const version = useMemo(
|
||||
() => getLatestVersion(name, compatibility, prereleases),
|
||||
[name, compatibility, prereleases]
|
||||
)
|
||||
|
||||
useEffect(() => {
|
||||
window.dispatchEvent(new Event('resize')) // scroll position for progress
|
||||
if (!initialized && version) {
|
||||
setIsError(false)
|
||||
fetch(`${baseUrl}/meta/${name}-${version}.json`)
|
||||
.then(res => res.json())
|
||||
.then(json => {
|
||||
.then((res) => res.json())
|
||||
.then((json) => {
|
||||
setMeta(formatModelMeta(json))
|
||||
})
|
||||
.catch(err => {
|
||||
.catch((err) => {
|
||||
setIsError(true)
|
||||
console.error(err)
|
||||
})
|
||||
|
|
@ -360,7 +363,7 @@ const Model = ({
|
|||
</p>
|
||||
<Table fixed>
|
||||
<tbody>
|
||||
{Object.keys(labels).map(pipe => {
|
||||
{Object.keys(labels).map((pipe) => {
|
||||
const labelNames = labels[pipe] || []
|
||||
const help = LABEL_SCHEME_META[pipe]
|
||||
return (
|
||||
|
|
@ -402,9 +405,9 @@ const Models = ({ pageContext, repo, children }) => {
|
|||
window.dispatchEvent(new Event('resize')) // scroll position for progress
|
||||
if (!initialized) {
|
||||
fetch(`${baseUrl}/compatibility.json`)
|
||||
.then(res => res.json())
|
||||
.then((res) => res.json())
|
||||
.then(({ spacy }) => setCompatibility(spacy))
|
||||
.catch(err => console.error(err))
|
||||
.catch((err) => console.error(err))
|
||||
setInitialized(true)
|
||||
}
|
||||
}, [initialized, baseUrl])
|
||||
|
|
@ -415,7 +418,7 @@ const Models = ({ pageContext, repo, children }) => {
|
|||
<StaticQuery
|
||||
query={query}
|
||||
render={({ site }) =>
|
||||
models.map(modelName => (
|
||||
models.map((modelName) => (
|
||||
<Model
|
||||
key={modelName}
|
||||
name={modelName}
|
||||
|
|
|
|||
|
|
@ -28,7 +28,7 @@ function getSlug(data) {
|
|||
function filterResources(resources, data) {
|
||||
const sorted = resources.sort((a, b) => a.id.localeCompare(b.id))
|
||||
if (!data || !data.isCategory) return sorted
|
||||
return sorted.filter(res => (res.category || []).includes(data.id))
|
||||
return sorted.filter((res) => (res.category || []).includes(data.id))
|
||||
}
|
||||
|
||||
const UniverseContent = ({ content = [], categories, theme, pageContext, mdxComponents }) => {
|
||||
|
|
@ -142,7 +142,13 @@ const UniverseContent = ({ content = [], categories, theme, pageContext, mdxComp
|
|||
The Universe database is open-source and collected in a simple JSON file.
|
||||
For more details on the formats and available fields, see the documentation.
|
||||
Looking for inspiration your own spaCy plugin or extension? Check out the
|
||||
<Link to={"https://github.com/explosion/spaCy/discussions/categories/new-features-project-ideas/"} hideIcon ws>
|
||||
<Link
|
||||
to={
|
||||
'https://github.com/explosion/spaCy/discussions/categories/new-features-project-ideas/'
|
||||
}
|
||||
hideIcon
|
||||
ws
|
||||
>
|
||||
project idea
|
||||
</Link>
|
||||
section in Discussions.
|
||||
|
|
@ -316,7 +322,7 @@ const Project = ({ data, components }) => (
|
|||
{data.category && (
|
||||
<p style={{ marginBottom: 0 }}>
|
||||
<Label>Categories</Label>
|
||||
{data.category.map(cat => (
|
||||
{data.category.map((cat) => (
|
||||
<Link to={`/universe/category/${cat}`} key={cat} ws>
|
||||
<InlineCode>{cat}</InlineCode>
|
||||
</Link>
|
||||
|
|
@ -330,7 +336,7 @@ const Project = ({ data, components }) => (
|
|||
const Universe = ({ pageContext, location, mdxComponents }) => (
|
||||
<StaticQuery
|
||||
query={query}
|
||||
render={data => {
|
||||
render={(data) => {
|
||||
const { universe, nightly, legacy } = data.site.siteMetadata
|
||||
const theme = nightly ? 'nightly' : legacy ? 'legacy' : pageContext.theme
|
||||
return (
|
||||
|
|
|
|||
|
|
@ -10,8 +10,8 @@ import { repo } from '../components/util'
|
|||
|
||||
function formatReleases(json) {
|
||||
return Object.values(json)
|
||||
.filter(release => release.name)
|
||||
.map(release => ({
|
||||
.filter((release) => release.name)
|
||||
.map((release) => ({
|
||||
title:
|
||||
release.name.split(': ').length === 2 ? release.name.split(': ')[1] : release.name,
|
||||
url: release.html_url,
|
||||
|
|
@ -34,14 +34,14 @@ const Changelog = () => {
|
|||
setIsError(false)
|
||||
setIsLoading(true)
|
||||
fetch(`https://api.github.com/repos/${repo}/releases`)
|
||||
.then(res => res.json())
|
||||
.then(json => {
|
||||
.then((res) => res.json())
|
||||
.then((json) => {
|
||||
const releases = formatReleases(json)
|
||||
setReleases(releases.filter(release => !release.pre))
|
||||
setPrereleases(releases.filter(release => release.pre))
|
||||
setReleases(releases.filter((release) => !release.pre))
|
||||
setPrereleases(releases.filter((release) => release.pre))
|
||||
setIsLoading(false)
|
||||
})
|
||||
.catch(err => {
|
||||
.catch((err) => {
|
||||
setIsLoading(false)
|
||||
setIsError(true)
|
||||
console.error(err)
|
||||
|
|
|
|||
|
|
@ -55,10 +55,10 @@ const Languages = () => (
|
|||
</Tr>
|
||||
</thead>
|
||||
<tbody>
|
||||
{withModels.map(model => (
|
||||
{withModels.map((model) => (
|
||||
<Language {...model} key={model.code} />
|
||||
))}
|
||||
{withoutModels.map(model => (
|
||||
{withoutModels.map((model) => (
|
||||
<Language {...model} key={model.code} />
|
||||
))}
|
||||
</tbody>
|
||||
|
|
|
|||
|
|
@ -13,10 +13,10 @@ const DEFAULT_CUDA = 'cuda-autodetect'
|
|||
const CUDA = {
|
||||
'8.0': 'cuda80',
|
||||
'9.0': 'cuda90',
|
||||
'9.1': 'cuda91',
|
||||
'9.2': 'cuda92',
|
||||
9.1: 'cuda91',
|
||||
9.2: 'cuda92',
|
||||
'10.0': 'cuda100',
|
||||
'10.1': 'cuda101',
|
||||
10.1: 'cuda101',
|
||||
'10.2, 11.0+': 'cuda-autodetect',
|
||||
}
|
||||
const LANG_EXTRAS = ['ja'] // only for languages with models
|
||||
|
|
@ -30,26 +30,26 @@ const QuickstartInstall = ({ id, title }) => {
|
|||
const [selectedModels, setModels] = useState(DEFAULT_MODELS)
|
||||
const [efficiency, setEfficiency] = useState(DEFAULT_OPT === 'efficiency')
|
||||
const setters = {
|
||||
hardware: v => (Array.isArray(v) ? setHardware(v[0]) : setCuda(v)),
|
||||
config: v => setTrain(v.includes('train')),
|
||||
hardware: (v) => (Array.isArray(v) ? setHardware(v[0]) : setCuda(v)),
|
||||
config: (v) => setTrain(v.includes('train')),
|
||||
models: setModels,
|
||||
optimize: v => setEfficiency(v.includes('efficiency')),
|
||||
platform: v => setPlatform(v[0]),
|
||||
os: v => setOs(v[0]),
|
||||
optimize: (v) => setEfficiency(v.includes('efficiency')),
|
||||
platform: (v) => setPlatform(v[0]),
|
||||
os: (v) => setOs(v[0]),
|
||||
}
|
||||
const showDropdown = {
|
||||
hardware: () => hardware === 'gpu',
|
||||
}
|
||||
const modelExtras = train ? selectedModels.filter(m => LANG_EXTRAS.includes(m)) : []
|
||||
const modelExtras = train ? selectedModels.filter((m) => LANG_EXTRAS.includes(m)) : []
|
||||
const apple = os === 'mac' && platform === 'arm'
|
||||
const pipExtras = [
|
||||
(hardware === 'gpu' && (platform !== 'arm' || os === 'linux')) && cuda,
|
||||
hardware === 'gpu' && (platform !== 'arm' || os === 'linux') && cuda,
|
||||
train && 'transformers',
|
||||
train && 'lookups',
|
||||
apple && 'apple',
|
||||
...modelExtras,
|
||||
]
|
||||
.filter(e => e)
|
||||
.filter((e) => e)
|
||||
.join(',')
|
||||
return (
|
||||
<StaticQuery
|
||||
|
|
@ -85,7 +85,7 @@ const QuickstartInstall = ({ id, title }) => {
|
|||
{ id: 'pip', title: 'pip', checked: true },
|
||||
!nightly ? { id: 'conda', title: 'conda' } : null,
|
||||
{ id: 'source', title: 'from source' },
|
||||
].filter(o => o),
|
||||
].filter((o) => o),
|
||||
},
|
||||
{
|
||||
id: 'hardware',
|
||||
|
|
@ -94,7 +94,7 @@ const QuickstartInstall = ({ id, title }) => {
|
|||
{ id: 'cpu', title: 'CPU', checked: DEFAULT_HARDWARE === 'cpu' },
|
||||
{ id: 'gpu', title: 'GPU', checked: DEFAULT_HARDWARE == 'gpu' },
|
||||
],
|
||||
dropdown: Object.keys(CUDA).map(id => ({
|
||||
dropdown: Object.keys(CUDA).map((id) => ({
|
||||
id: CUDA[id],
|
||||
title: `CUDA ${id}`,
|
||||
})),
|
||||
|
|
@ -113,8 +113,7 @@ const QuickstartInstall = ({ id, title }) => {
|
|||
{
|
||||
id: 'train',
|
||||
title: 'train models',
|
||||
help:
|
||||
'Check this if you plan to train your own models with spaCy to install extra dependencies and data resources',
|
||||
help: 'Check this if you plan to train your own models with spaCy to install extra dependencies and data resources',
|
||||
},
|
||||
],
|
||||
},
|
||||
|
|
@ -160,7 +159,10 @@ const QuickstartInstall = ({ id, title }) => {
|
|||
showDropdown={showDropdown}
|
||||
>
|
||||
<QS os="mac" hardware="gpu" platform="arm">
|
||||
# Note M1 GPU support is experimental, see <a href="https://github.com/explosion/thinc/issues/792">Thinc issue #792</a>
|
||||
# Note M1 GPU support is experimental, see{' '}
|
||||
<a href="https://github.com/explosion/thinc/issues/792">
|
||||
Thinc issue #792
|
||||
</a>
|
||||
</QS>
|
||||
<QS package="pip" config="venv">
|
||||
python -m venv .env
|
||||
|
|
@ -220,7 +222,8 @@ const QuickstartInstall = ({ id, title }) => {
|
|||
<QS package="source">cd spaCy</QS>
|
||||
<QS package="source">pip install -r requirements.txt</QS>
|
||||
<QS package="source">
|
||||
pip install --no-build-isolation --editable {train || hardware == 'gpu' ? `'.[${pipExtras}]'` : '.'}
|
||||
pip install --no-build-isolation --editable{' '}
|
||||
{train || hardware == 'gpu' ? `'.[${pipExtras}]'` : '.'}
|
||||
</QS>
|
||||
<QS config="train" package="conda" comment prompt={false}>
|
||||
# packages only available via pip
|
||||
|
|
|
|||
|
|
@ -60,7 +60,7 @@ const QuickstartInstall = ({ id, title, description, children }) => {
|
|||
const [efficiency, setEfficiency] = useState(DEFAULT_OPT === 'efficiency')
|
||||
const setters = {
|
||||
lang: setLang,
|
||||
optimize: v => setEfficiency(v.includes('efficiency')),
|
||||
optimize: (v) => setEfficiency(v.includes('efficiency')),
|
||||
}
|
||||
return (
|
||||
<StaticQuery
|
||||
|
|
|
|||
|
|
@ -10,7 +10,15 @@ const DEFAULT_LANG = 'en'
|
|||
const DEFAULT_HARDWARE = 'cpu'
|
||||
const DEFAULT_OPT = 'efficiency'
|
||||
const DEFAULT_TEXTCAT_EXCLUSIVE = true
|
||||
const COMPONENTS = ['tagger', 'morphologizer', 'trainable_lemmatizer', 'parser', 'ner', 'spancat', 'textcat']
|
||||
const COMPONENTS = [
|
||||
'tagger',
|
||||
'morphologizer',
|
||||
'trainable_lemmatizer',
|
||||
'parser',
|
||||
'ner',
|
||||
'spancat',
|
||||
'textcat',
|
||||
]
|
||||
const COMMENT = `# This is an auto-generated partial config. To use it with 'spacy train'
|
||||
# you can run spacy init fill-config to auto-fill all default settings:
|
||||
# python -m spacy init fill-config ./base_config.cfg ./config.cfg`
|
||||
|
|
@ -25,7 +33,7 @@ const DATA = [
|
|||
id: 'components',
|
||||
title: 'Components',
|
||||
help: 'Pipeline components to train. Requires training data for those annotations.',
|
||||
options: COMPONENTS.map(id => ({ id, title: id })),
|
||||
options: COMPONENTS.map((id) => ({ id, title: id })),
|
||||
multiple: true,
|
||||
},
|
||||
{
|
||||
|
|
@ -52,8 +60,7 @@ const DATA = [
|
|||
{
|
||||
id: 'optimize',
|
||||
title: 'Optimize for',
|
||||
help:
|
||||
'Optimize for efficiency (faster inference, smaller model, lower memory consumption) or higher accuracy (potentially larger & slower model). Will impact the choice of architecture, pretrained weights and hyperparameters.',
|
||||
help: 'Optimize for efficiency (faster inference, smaller model, lower memory consumption) or higher accuracy (potentially larger & slower model). Will impact the choice of architecture, pretrained weights and hyperparameters.',
|
||||
options: [
|
||||
{ id: 'efficiency', title: 'efficiency', checked: DEFAULT_OPT === 'efficiency' },
|
||||
{ id: 'accuracy', title: 'accuracy', checked: DEFAULT_OPT === 'accuracy' },
|
||||
|
|
@ -71,16 +78,18 @@ export default function QuickstartTraining({ id, title, download = 'base_config.
|
|||
|
||||
function updateComponents(value, isExclusive) {
|
||||
_setComponents(value)
|
||||
const updated = value.map(c => (c === 'textcat' && !isExclusive ? 'textcat_multilabel' : c))
|
||||
const updated = value.map((c) =>
|
||||
c === 'textcat' && !isExclusive ? 'textcat_multilabel' : c
|
||||
)
|
||||
setComponents(updated)
|
||||
}
|
||||
|
||||
const setters = {
|
||||
lang: setLang,
|
||||
components: v => updateComponents(v, textcatExclusive),
|
||||
components: (v) => updateComponents(v, textcatExclusive),
|
||||
hardware: setHardware,
|
||||
optimize: setOptimize,
|
||||
textcat: v => {
|
||||
textcat: (v) => {
|
||||
const isExclusive = v.includes('exclusive')
|
||||
setTextcatExclusive(isExclusive)
|
||||
updateComponents(_components, isExclusive)
|
||||
|
|
@ -101,7 +110,7 @@ export default function QuickstartTraining({ id, title, download = 'base_config.
|
|||
const rawContent = `${COMMENT}\n${rawStr}`
|
||||
const displayContent = highlightCode('ini', rawContent)
|
||||
.split('\n')
|
||||
.map(line => (line.startsWith('#') ? `<span class="token comment">${line}</span>` : line))
|
||||
.map((line) => (line.startsWith('#') ? `<span class="token comment">${line}</span>` : line))
|
||||
.join('\n')
|
||||
return (
|
||||
<StaticQuery
|
||||
|
|
@ -116,7 +125,7 @@ export default function QuickstartTraining({ id, title, download = 'base_config.
|
|||
}))
|
||||
.sort((a, b) => a.title.localeCompare(b.title))
|
||||
if (!_components.includes('textcat')) {
|
||||
data = data.map(field =>
|
||||
data = data.map((field) =>
|
||||
field.id === 'textcat' ? { ...field, hidden: true } : field
|
||||
)
|
||||
}
|
||||
|
|
|
|||
|
|
@ -53,7 +53,7 @@ const Card = ({ style = {}, children }) => (
|
|||
|
||||
export const Colors = () => (
|
||||
<Grid cols={4} narrow>
|
||||
{Object.keys(colors).map(name => (
|
||||
{Object.keys(colors).map((name) => (
|
||||
<Card key={name} style={{ height: 80, background: colors[name] }}>
|
||||
<Label>{name}</Label>
|
||||
</Card>
|
||||
|
|
@ -62,7 +62,7 @@ export const Colors = () => (
|
|||
)
|
||||
|
||||
export const Patterns = () => {
|
||||
const imgStyle = name => ({
|
||||
const imgStyle = (name) => ({
|
||||
height: 125,
|
||||
background: `url(${patterns[name]}) center/150% repeat`,
|
||||
})
|
||||
|
|
@ -70,7 +70,7 @@ export const Patterns = () => {
|
|||
const linkStyle = { color: 'var(--color-dark)' }
|
||||
return (
|
||||
<Grid cols={3} narrow>
|
||||
{Object.keys(patterns).map(name => (
|
||||
{Object.keys(patterns).map((name) => (
|
||||
<Card key={name} style={imgStyle(name)}>
|
||||
<Label>{name}</Label>
|
||||
<span style={textStyle}>
|
||||
|
|
|
|||
Loading…
Reference in New Issue
Block a user