mirror of
https://github.com/explosion/spaCy.git
synced 2024-11-14 13:47:13 +03:00
adding spacy-universal-sentence-encoder (#5534)
* adding spacy-universal-sentence-encoder * update affiliation * updated code example
This commit is contained in:
parent
0d3cfe155f
commit
487be097ea
4
.github/contributors/MartinoMensio.md
vendored
4
.github/contributors/MartinoMensio.md
vendored
|
@ -99,8 +99,8 @@ mark both statements:
|
||||||
| Field | Entry |
|
| Field | Entry |
|
||||||
|------------------------------- | -------------------- |
|
|------------------------------- | -------------------- |
|
||||||
| Name | Martino Mensio |
|
| Name | Martino Mensio |
|
||||||
| Company name (if applicable) | Polytechnic University of Turin |
|
| Company name (if applicable) | The Open University |
|
||||||
| Title or role (if applicable) | Student |
|
| Title or role (if applicable) | PhD Student |
|
||||||
| Date | 17 November 2017 |
|
| Date | 17 November 2017 |
|
||||||
| GitHub username | MartinoMensio |
|
| GitHub username | MartinoMensio |
|
||||||
| Website (optional) | https://martinomensio.github.io/ |
|
| Website (optional) | https://martinomensio.github.io/ |
|
||||||
|
|
|
@ -1,5 +1,29 @@
|
||||||
{
|
{
|
||||||
"resources": [
|
"resources": [
|
||||||
|
{
|
||||||
|
"id": "spacy-universal-sentence-encoder",
|
||||||
|
"title": "SpaCy - Universal Sentence Encoder",
|
||||||
|
"slogan": "Make use of Google's Universal Sentence Encoder directly within SpaCy",
|
||||||
|
"description": "This library lets you use Universal Sentence Encoder embeddings of Docs, Spans and Tokens directly from TensorFlow Hub",
|
||||||
|
"github": "MartinoMensio/spacy-universal-sentence-encoder-tfhub",
|
||||||
|
"code_example": [
|
||||||
|
"import spacy_universal_sentence_encoder",
|
||||||
|
"load one of the models: ['en_use_md', 'en_use_lg', 'xx_use_md', 'xx_use_lg']",
|
||||||
|
"nlp = spacy_universal_sentence_encoder.load_model('en_use_lg')",
|
||||||
|
"# get two documents",
|
||||||
|
"doc_1 = nlp('Hi there, how are you?')",
|
||||||
|
"doc_2 = nlp('Hello there, how are you doing today?')",
|
||||||
|
"# use the similarity method that is based on the vectors, on Doc, Span or Token",
|
||||||
|
"print(doc_1.similarity(doc_2[0:7]))"
|
||||||
|
],
|
||||||
|
"category": ["models", "pipeline"],
|
||||||
|
"author": "Martino Mensio",
|
||||||
|
"author_links": {
|
||||||
|
"twitter": "MartinoMensio",
|
||||||
|
"github": "MartinoMensio",
|
||||||
|
"website": "https://martinomensio.github.io"
|
||||||
|
}
|
||||||
|
},
|
||||||
{
|
{
|
||||||
"id": "whatlies",
|
"id": "whatlies",
|
||||||
"title": "whatlies",
|
"title": "whatlies",
|
||||||
|
|
Loading…
Reference in New Issue
Block a user