wikipedia2vec | A tool for learning vector representations of words | Natural Language Processing library

by wikipedia2vec Python Version: v1.0.5 License: Non-SPDX

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kandi X-RAY | wikipedia2vec Summary

wikipedia2vec is a Python library typically used in Artificial Intelligence, Natural Language Processing, Bert applications. wikipedia2vec has no bugs, it has no vulnerabilities, it has build file available and it has medium support. However wikipedia2vec has a Non-SPDX License. You can download it from GitHub.

Wikipedia2Vec is a tool used for obtaining embeddings (or vector representations) of words and entities (i.e., concepts that have corresponding pages in Wikipedia) from Wikipedia. It is developed and maintained by [Studio Ousia] This tool enables you to learn embeddings of words and entities simultaneously, and places similar words and entities close to one another in a continuous vector space. Embeddings can be easily trained by a single command with a publicly available Wikipedia dump as input. This tool implements the [conventional skip-gram model] to learn the embeddings of words, and its extension proposed in [Yamada et al. (2016)] to learn the embeddings of entities. An empirical comparison between Wikipedia2Vec and existing embedding tools (i.e., FastText, Gensim, RDF2Vec, and Wiki2vec) is available [here] Documentation are available online at [

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wikipedia2vec has a medium active ecosystem.

It has 850 star(s) with 94 fork(s). There are 35 watchers for this library.

It had no major release in the last 12 months.

There are 4 open issues and 60 have been closed. On average issues are closed in 11 days. There are 3 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of wikipedia2vec is v1.0.5

Quality

wikipedia2vec has 0 bugs and 0 code smells.

Security

wikipedia2vec has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

wikipedia2vec code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

wikipedia2vec has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

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wikipedia2vec releases are available to install and integrate.

Build file is available. You can build the component from source.

Installation instructions are not available. Examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi has reviewed wikipedia2vec and discovered the below as its top functions. This is intended to give you an instant insight into wikipedia2vec implemented functionality, and help decide if they suit your requirements.

List all the cpp files in the package directory
Train an embedding
Train the model
Generate features for a given text corpus
Perform a single step
Detect mentions in text
Evaluate a model
Return a tokenizer instance
Get tokenizer for given language
Returns a sentence detector object
Returns a list of Instances
Train a classifier
Load R8 dataset
Load a 20ng dataset
Normalize text
Sets up tensorflow
Build a MentionDB
Build a dictionary from a DumpDB file
Build an Entity Linker
Builds entities from a database

Get all kandi verified functions for this library.

wikipedia2vec Key Features

No Key Features are available at this moment for wikipedia2vec.

wikipedia2vec Examples and Code Snippets

No Code Snippets are available at this moment for wikipedia2vec.

Community Discussions

Trending Discussions on wikipedia2vec

How to fix unpickling key error when loading word2vec (gensim)?

QUESTION

How to fix unpickling key error when loading word2vec (gensim)?

Asked 2020-Aug-13 at 02:02

I am trying to load a pre-trained word2vec model in pkl format taken from here

The line of code I use to load it:

...

ANSWER

Answered 2020-Aug-13 at 02:02

Per your link https://wikipedia2vec.github.io/wikipedia2vec/pretrained/ these are to be loaded using that library's Wikipedia2Vec.load() method.

Gensim's .load() methods should only be used with files saved directly from Gensim model objects.

The Wikipedia2Vec project does say that their .txt file formats would load with .load_word2vec_format(), so you could also try that - but with one of their .txt format files.

Their full model .pkl files are only going to work with their class's own loading function.

Source https://stackoverflow.com/questions/63385272

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

Vulnerabilities

No vulnerabilities reported

Install wikipedia2vec

You can download it from GitHub.
You can use wikipedia2vec like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

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For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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