wordvectors | Pre-trained word vectors of 30 languages | Natural Language Processing library

 by   Kyubyong Python Version: Current License: MIT

kandi X-RAY | wordvectors Summary

kandi X-RAY | wordvectors Summary

wordvectors is a Python library typically used in Artificial Intelligence, Natural Language Processing applications. wordvectors has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. However wordvectors build file is not available. You can download it from GitHub.

Pre-trained word vectors of 30+ languages
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            kandi-support Support

              wordvectors has a medium active ecosystem.
              It has 2013 star(s) with 381 fork(s). There are 87 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              There are 12 open issues and 7 have been closed. On average issues are closed in 10 days. There are 4 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of wordvectors is current.

            kandi-Quality Quality

              wordvectors has 0 bugs and 0 code smells.

            kandi-Security Security

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

            kandi-License License

              wordvectors 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

              wordvectors releases are not available. You will need to build from source code and install.
              wordvectors has no build file. You will be need to create the build yourself to build the component from source.
              wordvectors saves you 66 person hours of effort in developing the same functionality from scratch.
              It has 172 lines of code, 6 functions and 2 files.
              It has low code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed wordvectors and discovered the below as its top functions. This is intended to give you an instant insight into wordvectors implemented functionality, and help decide if they suit your requirements.
            • Cleans text .
            • Generate a list of word vectors .
            • Build corpus .
            • Split a sentence .
            • Split a sentence .
            • Returns the minimum count of the top kth word .
            Get all kandi verified functions for this library.

            wordvectors Key Features

            No Key Features are available at this moment for wordvectors.

            wordvectors Examples and Code Snippets

            11.其他学习资料
            Pythondot img1Lines of Code : 65dot img1no licencesLicense : No License
            copy iconCopy
            数据概览:7000 多条酒店评论数据,5000 多条正向评论,2000 多条负向评论
            
            下载地址:
            
            https://github.com/SophonPlus/ChineseNlpCorpus/blob/master/datasets/ChnSentiCorp_htl_all/intro.ipynb
            
            数据概览:某外卖平台收集的用户评价,正向 4000 条,负向 约 8000 条
            
            下载地址:
            
            https://github.com/SophonPlus/ChineseNlpCorpus/bl  
            Core NLP algorithms for Vietnamese,2. Word Embedding
            Pythondot img2Lines of Code : 21dot img2no licencesLicense : No License
            copy iconCopy
            from word_embedding.utils import download_html
            url_path = "https://dantri.com.vn/su-kien/anh-huong-bao....htm"
            output_path = "data/word_embedding/real/html/html_data.txt"
            download_html(url_path, output_path, should_clean=True)
            
            input_dir = 'data/word  
            udpipe.models.ud - liberal udpipe models,Reproducibility
            Rdot img3Lines of Code : 4dot img3License : Non-SPDX (NOASSERTION)
            copy iconCopy
            ## First make sure you have the necessary R packages installed
            install.packages("udpipe")
            devtools::install_github("bmschmidt/wordVectors")
            
            Rscript src/dutch/train.R > src/dutch/train.log
              

            Community Discussions

            QUESTION

            Can't load the pre-trained word2vec of korean language
            Asked 2021-Dec-23 at 07:58

            I would like to download and load the pre-trained word2vec for analyzing Korean text.

            I download the pre-trained word2vec here: https://drive.google.com/file/d/0B0ZXk88koS2KbDhXdWg1Q2RydlU/view?resourcekey=0-Dq9yyzwZxAqT3J02qvnFwg from the Github Pre-trained word vectors of 30+ languages: https://github.com/Kyubyong/wordvectors

            My gensim version is 4.1.0, thus I used: KeyedVectors.load_word2vec_format('./ko.bin', binary=False) to load the model. But there was an error that :

            UnicodeDecodeError: 'utf-8' codec can't decode byte 0x80 in position 0: invalid start byte

            I already tried many options including in stackoverflow and Github, but it still not work well. Would you mind letting me the suitable solution?

            Thanks,

            ...

            ANSWER

            Answered 2021-Dec-23 at 07:58

            While the page at https://github.com/Kyubyong/wordvectors isn't clear about the formats this author has chosen, by looking at their source code at...

            https://github.com/Kyubyong/wordvectors/blob/master/make_wordvectors.py#L61

            ...shows it using the Gensim model .save() method.

            Such saved models should be reloaded using the .load() class method of the same model class. For example, if a Word2Vec model was saved with...

            Source https://stackoverflow.com/questions/70458726

            QUESTION

            100% training and valuation accuracy, tried gradient clipping too
            Asked 2020-Jun-10 at 13:30

            I get always 100% training and validation accuracies. Here's how it looks:

            ...

            ANSWER

            Answered 2020-Jun-10 at 12:39

            You initialize decoder_targets_one_hot as vectors of zeros, but do not set the index of true class as 1 anywhere. So, basically the target vectors are not one-hot vectors. The model tries to learn same target for all inputs, i.e. the vector of zeros.

            Source https://stackoverflow.com/questions/62303604

            QUESTION

            Models generate different results when moving to Azure Machine Learning Studio
            Asked 2020-Jun-07 at 01:37

            We developed a Jupyter Notebook in a local machine to train models with the Python (V3) libraries sklearn and gensim. As we set the random_state variable to a fixed integer, the results were always the same.

            After this, we tried moving the notebook to a workspace in Azure Machine Learning Studio (classic), but the results differ even if we leave the random_state the same.

            As suggested in the following links, we installed the same libraries versions and checked the MKL version was the same and the MKL_CBWR variable was set to AUTO.

            t-SNE generates different results on different machines

            Same Python code, same data, different results on different machines

            Still, we are not able to get the same results.

            What else should we check or why is this happening?

            Update

            If we generate a pkl file in the local machine and import it in AML, the results are the same (as the intention of the pkl file is).

            Still, we are looking to get the same results (if possible) without importing the pkl file.

            Library versions

            ...

            ANSWER

            Answered 2020-Jun-07 at 01:37

            Definitely empathize with the issue you're having. Every data scientist has struggled with this at some point.

            The hard truth I have for you is that Azure ML Studio (classic) isn't really capable of solving this "works on my machine" problem. However, the good news is that Azure ML Service is incredible at it. Studio classic doesn't let you define custom environments deterministically, only add and remove packages (and not so well even at that)

            Because ML Service's execution is built on top of Docker containers and conda environments, you can feel more confident in repeated results. I highly recommend you take the time to learn it (and I'm also happy to debug any issues that come up). Azure's MachineLearningNotebooks repo has a lot of great tutorials for getting started.

            I spent two hours making a proof of concept that demonstrate how ML Service solves the problem you're having by synthesizing:

            I'm no T-SNE expert, but from the screenshot below, you can see that the t-sne outputs are the same when I run the script locally and remotely. This might be possible with Studio classic, but it would be hard to guarantee that it will always work.

            Source https://stackoverflow.com/questions/62235365

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

            Vulnerabilities

            No vulnerabilities reported

            Install wordvectors

            You can download it from GitHub.
            You can use wordvectors 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 .
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            CLONE
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            https://github.com/Kyubyong/wordvectors.git

          • CLI

            gh repo clone Kyubyong/wordvectors

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            git@github.com:Kyubyong/wordvectors.git

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