Tokenizer | A tokenizer for Icelandic text | Natural Language Processing library

by mideind Python Version: 3.4.3 License: Non-SPDX

X-Ray Key Features Code Snippets Community Discussions(10)Vulnerabilities Install Support

kandi X-RAY | Tokenizer Summary

Tokenizer is a Python library typically used in Artificial Intelligence, Natural Language Processing, Bert applications. Tokenizer has no bugs, it has no vulnerabilities, it has build file available and it has low support. However Tokenizer has a Non-SPDX License. You can install using 'pip install Tokenizer' or download it from GitHub, PyPI.

A tokenizer for Icelandic text

Support

Quality

Security

License

Reuse

Support

Tokenizer has a low active ecosystem.

It has 27 star(s) with 6 fork(s). There are 10 watchers for this library.

It had no major release in the last 12 months.

There are 4 open issues and 14 have been closed. On average issues are closed in 120 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of Tokenizer is 3.4.3

Quality

Tokenizer has 0 bugs and 0 code smells.

Security

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

Tokenizer code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

Tokenizer 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.

Reuse

Tokenizer releases are available to install and integrate.

Deployable package is available in PyPI.

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

Tokenizer saves you 1851 person hours of effort in developing the same functionality from scratch.

It has 4086 lines of code, 99 functions and 8 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

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

Tokenize a string
Define a date token
Helper function for dates
Parse date and time series
Parse abbreviation
Add an abbreviation
Split at pos
Read file contents
Handle non - abbreviation
Mark paragraphs

Get all kandi verified functions for this library.

Tokenizer Key Features

No Key Features are available at this moment for Tokenizer.

Tokenizer Examples and Code Snippets

No Code Snippets are available at this moment for Tokenizer.

Community Discussions

Trending Discussions on Tokenizer

Extracting multiple Wikipedia pages using Pythons Wikipedia

Hugging Face: NameError: name 'sentences' is not defined

Force BERT transformer to use CUDA

Save/Export a custom tokenizer from google colab notebook

MemoryError with FastApi and SpaCy

ValueError: nlp.add_pipe now takes the string name of the registered component factory, not a callable component

JAVA how to refer the file in Project

Understanding how gpt-2 tokenizes the strings

how to tokenize and search with special characters in ElasticSearch

Can't import spacy

QUESTION

Extracting multiple Wikipedia pages using Pythons Wikipedia

Asked 2021-Jun-15 at 13:10

I am not sure how to extract multiple pages from a search result using Pythons Wikipedia plugin. Some advice would be appreciated.

My code so far:

...

ANSWER

Answered 2021-Jun-15 at 13:10

You have done the hard part, the results are already in the results variable.

But the results need parsing by the wiki.page() nethod, which only takes one argument.

The solution? Use a loop to parse all results one by one.

The easiest way will be using for loops, but the list comprehension method is the best.

Replace the last two lines with the following:

Source https://stackoverflow.com/questions/67986624

QUESTION

Hugging Face: NameError: name 'sentences' is not defined

Asked 2021-Jun-14 at 15:16

I am following this tutorial here: https://huggingface.co/transformers/training.html - though, I am coming across an error, and I think the tutorial is missing an import, but i do not know which.

These are my current imports:

...

ANSWER

Answered 2021-Jun-14 at 15:08

The error states that you do not have a variable called sentences in the scope. I believe the tutorial presumes you already have a list of sentences and are tokenizing it.

Have a look at the documentation The first argument can be either a string or list of string or list of list of strings.

Source https://stackoverflow.com/questions/67972661

QUESTION

Force BERT transformer to use CUDA

Asked 2021-Jun-13 at 09:57

I want to force the Huggingface transformer (BERT) to make use of CUDA. nvidia-smi showed that all my CPU cores were maxed out during the code execution, but my GPU was at 0% utilization. Unfortunately, I'm new to the Hugginface library as well as PyTorch and don't know where to place the CUDA attributes device = cuda:0 or .to(cuda:0).

The code below is basically a customized part from german sentiment BERT working example

...

ANSWER

Answered 2021-Jun-12 at 16:19

You can make the entire class inherit torch.nn.Module like so:

Source https://stackoverflow.com/questions/67948945

QUESTION

Save/Export a custom tokenizer from google colab notebook

Asked 2021-Jun-12 at 09:28

I have a custom tokenizer and want to use it for prediction in Production API. How do I save/download the tokenizer?

This is my code trying to save it:

...

ANSWER

Answered 2021-Jun-12 at 09:28

Here is the situation, using a simple file to disentangle the issue from irrelevant specificities like pickle, Tensorflow, and tokenizers:

Source https://stackoverflow.com/questions/67936111

QUESTION

MemoryError with FastApi and SpaCy

Asked 2021-Jun-12 at 06:42

I am running a FastAPI (v0.63.0) web app that uses SpaCy (v3.0.5) for tokenizing input texts. After the web service has been running for a while, the total memory usage grows too big, and SpaCy throws MemoryErrors, results in 500 errors of the web service.

...

ANSWER

Answered 2021-Jun-12 at 06:42

The SpaCy tokenizer seems to cache each token in a map internally. Consequently, each new token increases the size of that map. Over time, more and more new tokens inevitably occur (although with decreasing speed, following Zipf's law). At some point, after having processed large numbers of texts, the token map will thus outgrow the available memory. With a large amount of available memory, of course this can be delayed for a very long time.

The solution I have chosen is to store the SpaCy model in a TTLCache and to reload it every hour, emptying the token map. This adds some extra computational cost for reloading the SpaCy model from, but that is almost negligible.

Source https://stackoverflow.com/questions/67777505

QUESTION

ValueError: nlp.add_pipe now takes the string name of the registered component factory, not a callable component

Asked 2021-Jun-10 at 07:41

The following link shows how to add custom entity rule where the entities span more than one token. The code to do that is below:

...

ANSWER

Answered 2021-Jun-09 at 17:49

You need to define your own method to instantiate the entity ruler:

Source https://stackoverflow.com/questions/67906945

QUESTION

JAVA how to refer the file in Project

Asked 2021-Jun-10 at 03:09

I am create a simple Java Project in my VS Code, and here is the project structure.

I want to refer the wordcount.txt in my code, but it fail to find the file.

Here is my test code:

...

ANSWER

Answered 2021-Jun-10 at 03:09

Application resources will become embedded resources by the time of deployment, so it is wise to start accessing them as if they were, right now. An embedded-resource must be accessed by URL rather than file. See the info. page for embedded resource for how to form the URL.

Thanks for your work, work with getResource. Here is the working code

Source https://stackoverflow.com/questions/67901604

QUESTION

Understanding how gpt-2 tokenizes the strings

Asked 2021-Jun-09 at 14:19

Using tutorials here , I wrote the following codes:

...

ANSWER

Answered 2021-Jun-09 at 14:19

You can call tokenizer.decode on the output of the tokenizer to get the words from its vocabulary under given indices:

Source https://stackoverflow.com/questions/67299510

QUESTION

how to tokenize and search with special characters in ElasticSearch

Asked 2021-Jun-09 at 00:03

I need texts like #tag1 quick brown fox #tag2 to be tokenized into #tag1, quick, brown, fox, #tag2, so I can search this text on any of the patterns #tag1, quick, brown, fox, #tag2 where the symbol # must be included in the search term. In my index mapping I have a text type field (to search on quick, brown, fox) with the keyword type subfield (to search on #tag), and when I use search term #tag it gives me only the match on the first token #tag1 but not on #tag1. I think what I need is a tokenizer that will produce word boundary tokens that inlcude special chars. Can someone suggest a solution?

...

ANSWER

Answered 2021-Jun-08 at 16:38

If you want to include # in your search, you should use different analyzer than standard analyzer because # will be removed during analyze phase. You can use whitespace analyzer to analyze your text field. Also for search you can use wildcard pattern:

Query:

Source https://stackoverflow.com/questions/67872605

QUESTION

Can't import spacy

Asked 2021-Jun-08 at 16:11

i've been trying to import spacy but everytime an error appears as a result. I used this line to install the package :

...

ANSWER

Answered 2021-Jun-08 at 16:11

The problem is that the file you are working in is named spacy.py, which is interfering with the spacy module. So you should rename your file to something other than "spacy".

Source https://stackoverflow.com/questions/67890652

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

Vulnerabilities

No vulnerabilities reported

Install Tokenizer

You can install using 'pip install Tokenizer' or download it from GitHub, PyPI.
You can use Tokenizer 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.

Support

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 .

Find more information at: