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added classy-classification package to spacy universe (#10393)

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* Update universe.json

added classy-classification to Spacy universe

* Update universe.json

added classy-classification to the spacy universe resources

* Update universe.json

corrected a small typo in json

* Update website/meta/universe.json

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* Update website/meta/universe.json

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* Update website/meta/universe.json

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* Update universe.json

processed merge feedback

* Update universe.json

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
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David Berenstein 2022-03-07 12:47:26 +01:00 committed by svlandeg
parent 56cb167e84
commit 98ebf50e84
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@ -2599,6 +2599,53 @@
}, },
"category": ["pipeline"] "category": ["pipeline"]
}, },
{
"id": "classyclassification",
"slogan": "A Python library for classy few-shot and zero-shot classification within spaCy.",
"description": "Huggingface does offer some nice models for few/zero-shot classification, but these are not tailored to multi-lingual approaches. Rasa NLU has a nice approach for this, but its too embedded in their codebase for easy usage outside of Rasa/chatbots. Additionally, it made sense to integrate sentence-transformers and Huggingface zero-shot, instead of default word embeddings. Finally, I decided to integrate with spaCy, since training a custom spaCy TextCategorizer seems like a lot of hassle if you want something quick and dirty.",
"github": "davidberenstein1957/classy-classification",
"pip": "classy-classification",
"code_example": [
"import spacy",
"import classy_classification",
"",
"data = {",
" \"furniture\": [\"This text is about chairs.\",",
" \"Couches, benches and televisions.\",",
" \"I really need to get a new sofa.\"],",
" \"kitchen\": [\"There also exist things like fridges.\",",
" \"I hope to be getting a new stove today.\",",
" \"Do you also have some ovens.\"]",
"}",
"",
"nlp = spacy.load('en_core_web_md')",
"",
"classification_type = \"spacy_few_shot\"",
"if classification_type == \"spacy_few_shot\":",
" nlp.add_pipe(\"text_categorizer\", ",
" config={\"data\": data, \"model\": \"spacy\"}",
" )",
"elif classification_type == \"sentence_transformer_few_shot\":",
" nlp.add_pipe(\"text_categorizer\", ",
" config={\"data\": data, \"model\": \"sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2\"}",
" )",
"elif classification_type == \"huggingface_zero_shot\":",
" nlp.add_pipe(\"text_categorizer\", ",
" config={\"data\": list(data.keys()), \"cat_type\": \"zero\", \"model\": \"facebook/bart-large-mnli\"}",
" )",
"",
"print(nlp(\"I am looking for kitchen appliances.\")._.cats)",
"print([doc._.cats for doc in nlp.pipe([\"I am looking for kitchen appliances.\"])])"
],
"author": "David Berenstein",
"author_links": {
"github": "davidberenstein1957",
"website": "https://www.linkedin.com/in/david-berenstein-1bab11105/"
},
"category": ["pipeline", "standalone"],
"tags": ["classification", "zero-shot", "few-shot", "sentence-transformers", "huggingface"],
"spacy_version": 3
},
{ {
"id": "blackstone", "id": "blackstone",
"title": "Blackstone", "title": "Blackstone",