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spaCy | Industrialstrength Natural Language Processing in Python | Natural Language Processing library

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kandi X-RAY | spaCy Summary

spaCy is a Python library typically used in Artificial Intelligence, Natural Language Processing, Deep Learning, Pytorch, Bert applications. spaCy has no vulnerabilities, it has build file available, it has a Permissive License and it has medium support. However spaCy has 8 bugs. You can download it from GitHub.
spaCy is a library for advanced Natural Language Processing in Python and Cython. It's built on the very latest research, and was designed from day one to be used in real products. spaCy comes with pretrained pipelines and currently supports tokenization and training for 60+ languages. It features state-of-the-art speed and neural network models for tagging, parsing, named entity recognition, text classification and more, multi-task learning with pretrained transformers like BERT, as well as a production-ready training system and easy model packaging, deployment and workflow management. spaCy is commercial open-source software, released under the MIT license.

kandi-support Support

  • spaCy has a medium active ecosystem.
  • It has 23063 star(s) with 3786 fork(s). There are 559 watchers for this library.
  • There were 7 major release(s) in the last 6 months.
  • There are 84 open issues and 4990 have been closed. On average issues are closed in 32 days. There are 15 open pull requests and 0 closed requests.
  • It has a neutral sentiment in the developer community.
  • The latest version of spaCy is v3.1.6

quality kandi Quality

  • spaCy has 8 bugs (4 blocker, 0 critical, 3 major, 1 minor) and 1001 code smells.


  • spaCy has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
  • spaCy code analysis shows 0 unresolved vulnerabilities.
  • There are 93 security hotspots that need review.

license License

  • spaCy is licensed under the MIT License. This license is Permissive.
  • Permissive licenses have the least restrictions, and you can use them in most projects.


  • spaCy releases are available to install and integrate.
  • Build file is available. You can build the component from source.
  • Installation instructions, examples and code snippets are available.
Top functions reviewed by kandi - BETA

kandi has reviewed spaCy and discovered the below as its top functions. This is intended to give you an instant insight into spaCy implemented functionality, and help decide if they suit your requirements.

  • Print training data .
  • Create a Language instance from a config dictionary .
  • Package a pipeline .
  • Calculate the score for the given examples .
  • Convert a Conlluation sentence into a Doc object .
  • Train a language with an optimizer .
  • Removes whitespace from the example .
  • Train a language model .
  • Compile the gold data .
  • Convert input data to docs .

spaCy Key Features

Support for 60+ languages

Trained pipelines for different languages and tasks

Multi-task learning with pretrained transformers like BERT

Support for pretrained word vectors and embeddings

State-of-the-art speed

Production-ready training system

Linguistically-motivated tokenization

Components for named entity recognition, part-of-speech-tagging, dependency parsing, sentence segmentation, text classification, lemmatization, morphological analysis, entity linking and more

Easily extensible with custom components and attributes

Support for custom models in PyTorch, TensorFlow and other frameworks

Built in visualizers for syntax and NER

Easy model packaging, deployment and workflow management

Robust, rigorously evaluated accuracy

spaCy Examples and Code Snippets

  • pip
  • conda
  • Updating spaCy
  • ๐Ÿ“ฆ Download model packages
  • Loading and using models
  • โš’ Compile from source
  • ๐Ÿšฆ Run tests
  • Save and load nlp results in spacy
  • How to match repeating patterns in spacy?
  • Spacy tokenization add extra white space for dates with hyphen separator when I manually build the Doc
  • After installing scrubadub_spacy package, spacy.load("en_core_web_sm") not working OSError: [E053] Could not read config.cfg
  • Show NER Spacy Data in dataframe
  • How to use japanese engine in Spacy
  • Return all possible entity types from spaCy model?
  • Spacy: count occurrence for specific token in each sentence
  • How to install Tesseract OCR on Databricks
  • How to use existing huggingface-transformers model into spacy?


pip install -U pip setuptools wheel
pip install spacy

Community Discussions

Trending Discussions on spaCy
  • Error while loading vector from Glove in Spacy
  • Save and load nlp results in spacy
  • How to match repeating patterns in spacy?
  • Spacy adds words automatically to vocab?
  • Spacy tokenization add extra white space for dates with hyphen separator when I manually build the Doc
  • After installing scrubadub_spacy package, spacy.load("en_core_web_sm") not working OSError: [E053] Could not read config.cfg
  • Show NER Spacy Data in dataframe
  • How to get a description for each Spacy NER entity?
  • Do I need to do any text cleaning for Spacy NER?
  • How to use japanese engine in Spacy
Trending Discussions on spaCy


Error while loading vector from Glove in Spacy

Asked 2022-Mar-17 at 16:39

I am facing the following attribute error when loading glove model:

Code used to load model:

nlp = spacy.load('en_core_web_sm')
tokenizer = spacy.load('en_core_web_sm', disable=['tagger','parser', 'ner', 'textcat'])

Getting the following atribute error when trying to load the glove model:

AttributeError: 'spacy.vectors.Vectors' object has no attribute 'from_glove'

Have tried to search on StackOverflow and elsewhere but can't seem to find the solution. Thanks!

From pip list:

  • spacy version: 3.1.4
  • spacy-legacy 3.0.8
  • en-core-web-sm 3.1.0


Answered 2022-Mar-17 at 14:08

spacy version: 3.1.4 does not have the feature from_glove.

I was able to use nlp.vocab.vectors.from_glove() in spacy version: 2.2.4.

If you want, you can change your spacy version by using:

!pip install spacy==2.2.4 on your Jupyter cell.

Source https://stackoverflow.com/questions/71512064

Community Discussions, Code Snippets contain sources that include Stack Exchange Network


No vulnerabilities reported

Install spaCy

For detailed installation instructions, see the documentation.
Operating system: macOS / OS X ยท Linux ยท Windows (Cygwin, MinGW, Visual Studio)
Python version: Python 3.6+ (only 64 bit)
Package managers: pip ยท conda (via conda-forge)
Trained pipelines for spaCy can be installed as Python packages. This means that they're a component of your application, just like any other module. Models can be installed using spaCy's download command, or manually by pointing pip to a path or URL.


New to spaCy? Here's everything you need to know!. How to use spaCy and its features. ๐Ÿš€ New in v3.0. New features, backwards incompatibilities and migration guide. End-to-end workflows you can clone, modify and run. The detailed reference for spaCy's API. Download trained pipelines for spaCy. Plugins, extensions, demos and books from the spaCy ecosystem. Learn spaCy in this free and interactive online course. Our YouTube channel with video tutorials, talks and more. Changes and version history. How to contribute to the spaCy project and code base. Get a custom spaCy pipeline, tailor-made for your NLP problem by spaCy's core developers. Streamlined, production-ready, predictable and maintainable. Start by completing our 5-minute questionnaire to tell us what you need and we'll be in touch! Learn more โ†’.

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