Spacy is an advanced natural language library for text processing in python. Using it you can easily find the context of the text therefore very helpful for extracting meaningful information from the text. As the text can be of different languages and spacy is trained according to that. In this entire tutorial, you will learn how to install en_core_web_lg on your system.
What is en_core_web_lg?
en_core_web_lg is the trained pipeline for the English language. It is optimized for the CPU and contains components like ok2vec, tagger, parser, senter, ner, attribute_ruler, lemmatizer. Its file size is 741 MB as compared to en_core_web_md whose size is only 13 MB. It is the largest English model in size provided by Spacy.
How to install en_core_web_lg?
There are many coders that have asked data science learner to make a complete post on how to install en_core_web_lg on their system. In this section, you will know all the steps to install en_core_web_lg.
Step 1: Install Spacy
The first step is to install spacy on your system using the pip or pip3 command depending on your python version. If your version is 2. xx then use the pip command and if it is python 3. xx then use pip3.
To check the version of your python version use the below command.
For python 2. xx version
pip install -U spacy
For python 3. xx version
pip3 install -U spacy
Step 2: Install the en_core_web_lg
After installing spacy run the below command to download and install en_core_web_lg in your system. The syntax for downloading the model is below.
[model] is the name of the model you want to install. In our case the model name is en_core_web_lg.
python -m spacy download [model]
python -m spacy download en_core_web_lg
There is also another method to install the en_core_web_lg language model using the pip command. To do so you have to run the following command.
pip3 install https://github.com/explosion/spacy-models/releases/download/de_core_news_lg-3.2.0/de_core_news_lg-3.2.0-py3-none-any.whl
You can download more releases for other models from Github.
Spacy is the best package for implementing NLP tasks. You can tokenize, lemmatize , match documents using it. To do so you have to use various trained language models and en_core_web_lg is one of them. These are steps you will follow to install en_core_web_lg on your system. I hope you have liked this tutorial on installing en_core_web_lg.
If you have any doubt then you can contact us for more help.
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