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Update models.js
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@ -218,7 +218,7 @@ const Model = ({ name, langId, langName, baseUrl, repo, compatibility, hasExampl
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)}
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</tbody>
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</Table>
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<Grid cols={2} gutterBottom={hasInteractiveCode}>
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<Grid cols={2} gutterBottom={hasInteractiveCode || !!labels}>
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{accuracy &&
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accuracy.map(({ label, items }, i) =>
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!items ? null : (
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@ -260,6 +260,46 @@ const Model = ({ name, langId, langName, baseUrl, repo, compatibility, hasExampl
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].join('\n')}
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</CodeBlock>
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)}
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{labels && (
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<Accordion id={`${name}-labels`} title="Label Scheme">
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<p>
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The statistical components included in this model package assign the
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following labels. The labels are specific to the corpus that the model was
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trained on. To see the description of a label, you can use{' '}
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<Link to="/api/top-level#spacy.explain">
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<InlineCode>spacy.explain</InlineCode>
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</Link>
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.
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</p>
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<Table fixed>
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<tbody>
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{Object.keys(labels).map(pipe => {
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const labelNames = labels[pipe] || []
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const help = LABEL_SCHEME_META[pipe]
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return (
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<Tr key={pipe} evenodd={false} key={pipe}>
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<Td style={{ width: '20%' }}>
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<Label>
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{pipe} {help && <Help>{help}</Help>}
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</Label>
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</Td>
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<Td>
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{labelNames.map((label, i) => (
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<>
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{i > 0 && ', '}
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<InlineCode wrap key={label}>
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{label}
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</InlineCode>
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</>
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))}
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</Td>
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</Tr>
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)
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})}
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</tbody>
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</Table>
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</Accordion>
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)}
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</Section>
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)
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}
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