tokenizer | Natural Language Tokenizers implemented in Go | Natural Language Processing library

 by   srom Go Version: Current License: MIT

kandi X-RAY | tokenizer Summary

kandi X-RAY | tokenizer Summary

tokenizer is a Go library typically used in Artificial Intelligence, Natural Language Processing applications. tokenizer has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

Implementation of various natural language tokenizers in Go.
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            kandi-support Support

              tokenizer has a low active ecosystem.
              It has 5 star(s) with 0 fork(s). There are 2 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              tokenizer has no issues reported. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of tokenizer is current.

            kandi-Quality Quality

              tokenizer has no bugs reported.

            kandi-Security Security

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

            kandi-License License

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

            kandi-Reuse Reuse

              tokenizer releases are not available. You will need to build from source code and install.

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            tokenizer Key Features

            No Key Features are available at this moment for tokenizer.

            tokenizer Examples and Code Snippets

            fileTypeFromTokenizer(tokenizer)
            npmdot img1Lines of Code : 26dot img1no licencesLicense : No License
            copy iconCopy
            import {makeTokenizer} from '@tokenizer/http';
            import {fileTypeFromTokenizer} from 'file-type';
            
            const audioTrackUrl = 'https://test-audio.netlify.com/Various%20Artists%20-%202009%20-%20netBloc%20Vol%2024_%20tiuqottigeloot%20%5BMP3-V2%5D/01%20-%20Dia  
            Tokenizer with custom configuration .
            javadot img2Lines of Code : 26dot img2License : Permissive (MIT License)
            copy iconCopy
            public static List streamTokenizerWithCustomConfiguration(Reader reader) throws IOException {
                    StreamTokenizer streamTokenizer = new StreamTokenizer(reader);
                    List tokens = new ArrayList<>();
            
                    streamTokenizer.wordChars('!'  
            Read stream tokenizer with default configuration .
            javadot img3Lines of Code : 22dot img3License : Permissive (MIT License)
            copy iconCopy
            public static List streamTokenizerWithDefaultConfiguration(Reader reader) throws IOException {
                    StreamTokenizer streamTokenizer = new StreamTokenizer(reader);
                    List tokens = new ArrayList<>();
            
                    int currentToken = streamTok  
            Get the model and tokenizer for a language model .
            pythondot img4Lines of Code : 13dot img4License : Permissive (MIT License)
            copy iconCopy
            def get_translation_model_and_tokenizer(src_lang, dst_lang):
              """
              Given the source and destination languages, returns the appropriate model
              See the language codes here: https://developers.google.com/admin-sdk/directory/v1/languages
              For the 3-c  

            Community Discussions

            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 download it from GitHub.

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            gh repo clone srom/tokenizer

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