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Update universe.json [ci skip]

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Ines Montani 2019-08-05 14:30:07 +02:00
parent e1a935d71c
commit 0f740fad1a
1 changed files with 26 additions and 2 deletions
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website/meta/universe.json
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@ -758,7 +758,7 @@
],
"category": ["pipeline", "standalone", "visualizers"],
"tags": ["vectors"],
"author": "Explosion AI",
"author": "Explosion",
"author_links": {
"twitter": "explosion_ai",
"github": "explosion",
@ -918,7 +918,7 @@
],
"code_language": "bash",
"category": ["standalone", "training"],
"author": "Explosion AI",
"author": "Explosion",
"author_links": {
"twitter": "explosion_ai",
"github": "explosion",
@ -1559,6 +1559,30 @@
"author_links": {
"github": "richardpaulhudson"
}
},
{
"id": "spacy-pytorch-transformers",
"title": "spacy-pytorch-transformers",
"slogan": "spaCy pipelines for pre-trained BERT, XLNet and GPT-2",
"description": "This package provides spaCy model pipelines that wrap [Hugging Face's `pytorch-transformers`](https://github.com/huggingface/pytorch-transformers) package, so you can use them in spaCy. The result is convenient access to state-of-the-art transformer architectures, such as BERT, GPT-2, XLNet, etc.",
"github": "explosion/spacy-pytorch-transformers",
"url": "https://explosion.ai/blog/spacy-pytorch-transformers",
"pip": "spacy-pytorch-transformers",
"category": ["pipeline", "models", "research"],
"code_example": [
"import spacy",
"",
"nlp = spacy.load(\"en_pytt_bertbaseuncased_lg\")",
"doc = nlp(\"Apple shares rose on the news. Apple pie is delicious.\")",
"print(doc[0].similarity(doc[7]))",
"print(doc._.pytt_last_hidden_state.shape)"
],
"author": "Explosion",
"author_links": {
"twitter": "explosion_ai",
"github": "explosion",
"website": "https://explosion.ai"
}
}
],