sentencepiece | Unsupervised text tokenizer for Neural Network | Natural Language Processing library

 by   google C++ Version: 0.2.0 License: Apache-2.0

kandi X-RAY | sentencepiece Summary

kandi X-RAY | sentencepiece Summary

sentencepiece is a C++ library typically used in Artificial Intelligence, Natural Language Processing, Deep Learning applications. sentencepiece has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. You can download it from GitHub.

Unsupervised text tokenizer for Neural Network-based text generation.
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            kandi-support Support

              sentencepiece has a medium active ecosystem.
              It has 7616 star(s) with 981 fork(s). There are 119 watchers for this library.
              There were 1 major release(s) in the last 12 months.
              There are 17 open issues and 610 have been closed. On average issues are closed in 135 days. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of sentencepiece is 0.2.0

            kandi-Quality Quality

              sentencepiece has 0 bugs and 0 code smells.

            kandi-Security Security

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

            kandi-License License

              sentencepiece is licensed under the Apache-2.0 License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              sentencepiece releases are available to install and integrate.
              Installation instructions, examples and code snippets are available.

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            sentencepiece Key Features

            No Key Features are available at this moment for sentencepiece.

            sentencepiece Examples and Code Snippets

            copy iconCopy
            ner = pipeline("ner", aggregation_strategy="simple", model="dbmdz/bert-large-cased-finetuned-conll03-english")  # Named Entity Recognition (NER)
            
            'NoneType' error when using PegasusTokenizer
            Pythondot img2Lines of Code : 2dot img2License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            pip install sentencepiece
            
            Using sentence transformers with limited access to internet
            Pythondot img3Lines of Code : 2dot img3License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            ['1_Pooling', 'config_sentence_transformers.json', 'tokenizer.json', 'tokenizer_config.json', 'modules.json', 'sentence_bert_config.json', 'pytorch_model.bin', 'special_tokens_map.json', 'config.json', 'train_script.py', 'data_config.json'
            TypeError: not a string | parameters in AutoTokenizer.from_pretrained()
            Pythondot img4Lines of Code : 2dot img4License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            tokenizer = AlbertTokenizer.from_pretrained('albert-base-v2')
            
            python packages not being installed on the virtual environment using ubuntu
            Pythondot img5Lines of Code : 2dot img5License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            pip3 install package_name --user
            
            Heroku: Compiled Slug Size is too large Python
            Pythondot img6Lines of Code : 4dot img6License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            heroku run bash -a 
            
            du -ha --max-depth 1 /app | sort -hr
            
            Wrong tensor type when trying to do the HuggingFace tutorial (pytorch)
            Pythondot img7Lines of Code : 4dot img7License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            model = AutoModelForSequenceClassification.from_pretrained(checkpoint, num_labels=1)
            
            model = AutoModelForSequenceClassification.from_pretrained(checkpoint, num_labels=2)
            
            Substring replacements based on replace and no-replace rules
            Pythondot img8Lines of Code : 27dot img8License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            replace_dict = ... # The code below assumes you already have this
            no_replace_dict = ...# The code below assumes you already have this
            text = ... # The text on input.
            
            def match_fun(match: re.Match):
                str_match: str = match.group()
            
                
            Substring replacements based on replace and no-replace rules
            Pythondot img9Lines of Code : 31dot img9License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            def replace_whole(sentence, replace_token, replace_with, dont_replace):
                rx = f"[\"\'\.,:; ]({replace_token})[\"\'\.,:; ]"
                iter = re.finditer(rx, sentence)
                out_sentence = ""
                found = []
                indices = []
                for m in iter:
               
            Error importing BERT: module 'tensorflow._api.v2.train' has no attribute 'Optimizer'
            Pythondot img10Lines of Code : 4dot img10License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            class AdamWeightDecayOptimizer(tf.train.Optimizer):
            
            class AdamWeightDecayOptimizer(tf.compat.v1.train.Optimizer):
            

            Community Discussions

            QUESTION

            HuggingFace Pipeline: UserWarning: `grouped_entities` is deprecated and will be removed in version v5.0.0. How to improve about this warning?
            Asked 2022-Apr-17 at 08:20

            I am using the following code

            ...

            ANSWER

            Answered 2022-Apr-17 at 08:19

            According to [HuggingFace]: Pipelines - class transformers.TokenClassificationPipeline (emphasis is mine):

            • grouped_entities (bool, optional, defaults to False) - DEPRECATED, use aggregation_strategy instead. Whether or not to group the tokens corresponding to the same entity together in the predictions or not.

            So, your line of code could be:

            Source https://stackoverflow.com/questions/71900161

            QUESTION

            Pip install results in this error " cl.exe' failed with exit code 2 "
            Asked 2022-Mar-27 at 07:11

            I've read all of the other questions on this error and frustratingly enough, none give a solution that works.

            If I run pip install sentencepiece in the cmd line, it gives me the following output.

            ...

            ANSWER

            Answered 2022-Feb-24 at 15:50

            I haven't seen this problem in Windows, but for Linux, I would normally reinstall Python after installing the dependencies (such as the MSVC thing). In that case this is especially helpful because I'm often rebuilding (compiling and other related steps) Python/Pip.

            Could also just be an error specific to the module and Python version combo you're trying.

            From a discussion in the comments:

            I have the pyenv-win version manager, so I was able to create venvs and test this for you. With Python 3.10.2, it fails; with Python 3.8.10, it's successful. So, yes, reinstalling does seem to be worthy of your time.

            Source https://stackoverflow.com/questions/71242919

            QUESTION

            How can I use custom tokenizer in opennmt transformer
            Asked 2022-Feb-11 at 09:07

            I'm tring to transformer for translation with opennmt-py.
            And I already have the tokenizer trained by sentencepiece(unigram).
            But I don't know how to use my custom tokenizer in training config yaml.
            I'm refering the site of opennmt-docs (https://opennmt.net/OpenNMT-py/examples/Translation.html).
            Here are my code and the error .

            ...

            ANSWER

            Answered 2022-Feb-11 at 09:07

            I got the answers.

            1. we can use tools/spm_to_vocab in onmt.
            2. train_from argument is the one.

            Source https://stackoverflow.com/questions/71062002

            QUESTION

            Colab: (0) UNIMPLEMENTED: DNN library is not found
            Asked 2022-Feb-08 at 19:27

            I have pretrained model for object detection (Google Colab + TensorFlow) inside Google Colab and I run it two-three times per week for new images I have and everything was fine for the last year till this week. Now when I try to run model I have this message:

            ...

            ANSWER

            Answered 2022-Feb-07 at 09:19

            It happened the same to me last friday. I think it has something to do with Cuda instalation in Google Colab but I don't know exactly the reason

            Source https://stackoverflow.com/questions/71000120

            QUESTION

            Using sentence transformers with limited access to internet
            Asked 2022-Jan-19 at 13:27

            I have access to the latest packages but I cannot access internet from my python enviroment.

            Package versions that I have are as below

            ...

            ANSWER

            Answered 2022-Jan-19 at 13:27

            Based on the things you mentioned, I checked the source code of sentence-transformers on Google Colab. After running the model and getting the files, I check the directory and I saw the pytorch_model.bin there.

            And according to sentence-transformers code: Link

            the flax_model.msgpack , rust_model.ot, tf_model.h5 are getting ignored when the it is trying to download.

            and these are the files that it downloads :

            Source https://stackoverflow.com/questions/70716702

            QUESTION

            HuggingFace AutoTokenizer | ValueError: Couldn't instantiate the backend tokenizer
            Asked 2022-Jan-14 at 14:10

            Goal: Amend this Notebook to work with albert-base-v2 model

            Error occurs in Section 1.3.

            Kernel: conda_pytorch_p36. I did Restart & Run All, and refreshed file view in working directory.

            There are 3 listed ways this error can be caused. I'm not sure which my case falls under.

            Section 1.3:

            ...

            ANSWER

            Answered 2022-Jan-14 at 14:09

            First, I had to pip install sentencepiece.

            However, in the same code line, I was getting an error with sentencepiece.

            Wrapping str() around both parameters yielded the same Traceback.

            Source https://stackoverflow.com/questions/70698407

            QUESTION

            TypeError: not a string | parameters in AutoTokenizer.from_pretrained()
            Asked 2022-Jan-14 at 14:07

            Goal: Amend this Notebook to work with albert-base-v2 model.

            Kernel: conda_pytorch_p36. I did Restart & Run All, and refreshed file view in working directory.

            In order to evaluate and to export this Quantised model, I need to setup a Tokenizer.

            Error occurs in Section 1.3.

            Both parameters in AutoTokenizer.from_pretrained() throw the same error.

            Section 1.3 Code:

            ...

            ANSWER

            Answered 2022-Jan-14 at 14:07

            Passing just the model name suffices.

            Source https://stackoverflow.com/questions/70709572

            QUESTION

            Tensorflow Object Detection API taking forever to install in a Google Colab and failing
            Asked 2021-Nov-19 at 00:16

            I am trying to install the Tensorflow Object Detection API on a Google Colab and the part that installs the API, shown below, takes a very long time to execute (in excess of one hour) and eventually fails to install.

            ...

            ANSWER

            Answered 2021-Nov-19 at 00:16

            I have solved this problem with

            Source https://stackoverflow.com/questions/70012098

            QUESTION

            python packages not being installed on the virtual environment using ubuntu
            Asked 2021-Aug-18 at 18:11

            I have a requirements.txt file which holds all information of my python packages I need for my Flask application. Here is what I did:

            1. python3 -m venv venv
            2. source venv/bin/activate
            3. sudo pip install -r requirements.txt

            When I tried to check if the packages were installed on the virtual environment using pip list, I do not see the packages. Can someone tell what went wrong?

            ...

            ANSWER

            Answered 2021-Aug-18 at 18:05

            If you want to use python3+ to install the packages try to use pip3 install package_name

            And to solve the errno 13 try to add --user at the end

            Source https://stackoverflow.com/questions/68837021

            QUESTION

            Heroku: Compiled Slug Size is too large Python
            Asked 2021-Jul-21 at 06:50

            I trying to deploy my app to heroku

            I have following deploying error

            ...

            ANSWER

            Answered 2021-Jul-21 at 06:50

            The maximum allowed slug size is 500MB. Slugs are an important aspect for heroku. When you git push to Heroku, your code is received by the slug compiler which transforms your repository into a slug.

            First of all, lets determine what all files are taking up a considerate amount of space in your slug. To do that, fire up your heroku cli and enter / access your dyno by typing the following:

            Source https://stackoverflow.com/questions/68464527

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

            Vulnerabilities

            No vulnerabilities reported

            Install sentencepiece

            The following tools and libraries are required to build SentencePiece:.
            cmake
            C++11 compiler
            gperftools library (optional, 10-40% performance improvement can be obtained.)
            You can download and install sentencepiece using the vcpkg dependency manager:. The sentencepiece port in vcpkg is kept up to date by Microsoft team members and community contributors. If the version is out of date, please create an issue or pull request on the vcpkg repository.

            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:

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            Install
          • PyPI

            pip install sentencepiece

          • CLONE
          • HTTPS

            https://github.com/google/sentencepiece.git

          • CLI

            gh repo clone google/sentencepiece

          • sshUrl

            git@github.com:google/sentencepiece.git

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