Tokenizer | Discord bot to find the tokens of other Discord bot | Bot library

 by   BenjaminUrquhart Java Version: Current License: No License

kandi X-RAY | Tokenizer Summary

kandi X-RAY | Tokenizer Summary

Tokenizer is a Java library typically used in Automation, Bot, Discord applications. Tokenizer has no bugs, it has no vulnerabilities and it has low support. However Tokenizer build file is not available. You can download it from GitHub.

Tokenizer - A Discord bot to find the tokens of other Discord bots on GitHub.
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            kandi-support Support

              Tokenizer has a low active ecosystem.
              It has 2 star(s) with 0 fork(s). There are no 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 0 bugs and 0 code smells.

            kandi-Security 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.

            kandi-License License

              Tokenizer does not have a standard license declared.
              Check the repository for any license declaration and review the terms closely.
              OutlinedDot
              Without a license, all rights are reserved, and you cannot use the library in your applications.

            kandi-Reuse Reuse

              Tokenizer releases are not available. You will need to build from source code and install.
              Tokenizer has no build file. You will be need to create the build yourself to build the component from source.

            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.
            • Handles a user request
            • Gets the GHPass password
            • Gets username
            • Handle a tokenizer
            • Evaluate an event for a guild message
            • Run token
            • Handles all registered commands
            • Gets OAuth token
            • Get OAuth token string
            • Gets OAuth URL
            • Main entry point
            • Put OAuth token
            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

            QUESTION

            TorchText Vocab TypeError: Vocab.__init__() got an unexpected keyword argument 'min_freq'
            Asked 2022-Apr-04 at 09:26

            I am working on a CNN Sentiment analysis machine learning model which uses the IMDb dataset provided by the Torchtext library. On one of my lines of code

            vocab = Vocab(counter, min_freq = 1, specials=('\', '\', '\', '\'))

            I am getting a TypeError for the min_freq argument even though I am certain that it is one of the accepted arguments for the function. I am also getting UserWarning Lambda function is not supported for pickle, please use regular python function or functools partial instead. Full code

            ...

            ANSWER

            Answered 2022-Apr-04 at 09:26

            As https://github.com/pytorch/text/issues/1445 mentioned, you should change "Vocab" to "vocab". I think they miss-type the legacy-to-new notebook.

            correct code:

            Source https://stackoverflow.com/questions/71652903

            QUESTION

            attributeerror: 'dataframe' object has no attribute 'data_type'
            Asked 2022-Jan-10 at 08:41

            I am getting the following error : attributeerror: 'dataframe' object has no attribute 'data_type'" . I am trying to recreate the code from this link which is based on this article with my own dataset which is similar to the article

            ...

            ANSWER

            Answered 2022-Jan-10 at 08:41

            The error means you have no data_type column in your dataframe because you missed this step

            Source https://stackoverflow.com/questions/70649379

            QUESTION

            How does Python interpreter actually interpret a program?
            Asked 2021-Dec-29 at 07:59

            Take a sample program:

            ...

            ANSWER

            Answered 2021-Dec-29 at 03:13

            The problem is not the order of interpretation, which is top to bottom as you expect; it's the scope. In Python, when referencing a global variable in a narrower function scope, if you modify the value, you must first tell the code that the global variable is the variable you are referencing, instead of a new local one. You do this with the global keyword. In this example, your program should actually look like this:

            Source https://stackoverflow.com/questions/70514761

            QUESTION

            How to calculate perplexity of a sentence using huggingface masked language models?
            Asked 2021-Dec-25 at 21:51

            I have several masked language models (mainly Bert, Roberta, Albert, Electra). I also have a dataset of sentences. How can I get the perplexity of each sentence?

            From the huggingface documentation here they mentioned that perplexity "is not well defined for masked language models like BERT", though I still see people somehow calculate it.

            For example in this SO question they calculated it using the function

            ...

            ANSWER

            Answered 2021-Dec-25 at 21:51

            There is a paper Masked Language Model Scoring that explores pseudo-perplexity from masked language models and shows that pseudo-perplexity, while not being theoretically well justified, still performs well for comparing "naturalness" of texts.

            As for the code, your snippet is perfectly correct but for one detail: in recent implementations of Huggingface BERT, masked_lm_labels are renamed to simply labels, to make interfaces of various models more compatible. I have also replaced the hard-coded 103 with the generic tokenizer.mask_token_id. So the snippet below should work:

            Source https://stackoverflow.com/questions/70464428

            QUESTION

            Fuzzy Matching in Elasticsearch gives different results in two different versions
            Asked 2021-Dec-17 at 18:25

            I have a mapping in elasticsearch with a field analyzer having tokenizer:

            ...

            ANSWER

            Answered 2021-Dec-09 at 11:28

            It's not related to ES version.

            Update max_expansions to more than 50.

            max_expansions : Maximum number of variations created.

            With 3 grams letter & digits as token_chars, ideal max_expansion will be (26 alphabets + 10 digits) * 3

            Source https://stackoverflow.com/questions/70255795

            QUESTION

            RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cpu and cuda:0! When predicting with my model
            Asked 2021-Nov-25 at 06:19

            I trained a model for sequence classification using transformers (BertForSequenceClassification) and I get the error:

            Expected all tensors to be on the same device, but found at least two devices, cpu and cuda:0! (when checking argument for argument index in method wrapper__index_select)

            I don't really get where is the problem, if it's on my model, on how I tokenize the data, or what.

            Here is my code:

            LOADING THE PRETRAINED MODEL

            ...

            ANSWER

            Answered 2021-Nov-25 at 06:19

            You did not move your model to device, only the data. You need to call model.to(device) before using it with data located on device.

            Source https://stackoverflow.com/questions/70102323

            QUESTION

            How can I check a confusion_matrix after fine-tuning with custom datasets?
            Asked 2021-Nov-24 at 13:26

            This question is the same with How can I check a confusion_matrix after fine-tuning with custom datasets?, on Data Science Stack Exchange.

            Background

            I would like to check a confusion_matrix, including precision, recall, and f1-score like below after fine-tuning with custom datasets.

            Fine tuning process and the task are Sequence Classification with IMDb Reviews on the Fine-tuning with custom datasets tutorial on Hugging face.

            After finishing the fine-tune with Trainer, how can I check a confusion_matrix in this case?

            An image of confusion_matrix, including precision, recall, and f1-score original site: just for example output image

            ...

            ANSWER

            Answered 2021-Nov-24 at 13:26

            What you could do in this situation is to iterate on the validation set(or on the test set for that matter) and manually create a list of y_true and y_pred.

            Source https://stackoverflow.com/questions/68691450

            QUESTION

            Pyodide filesystem for NLTK resources : missing files
            Asked 2021-Nov-14 at 22:03

            I am trying to use NLTK in browser, thanks to pyodide. Pyodide starts well, manages to load NLTK, print its version.

            Nevertheless, while the package downloading seems fine, when invoking nltk.sent_tokenize(str), NLTK raises the error that it can't find the package "punkt".

            I would say the downloaded resource is lost somewhere, but I didn't understand well how Pyodide / WebAssembly manage files. Any insights ?

            Simple version:

            ...

            ANSWER

            Answered 2021-Sep-02 at 14:53

            Short answer is that downloading files with Python currently won't work in Pyodide because http.client, requests etc require POSIX sockets which are not supported in the browser VM.

            It's curious that nltk.download doesn't error though -- it should have.

            The workaround is to manually download the needed resources, for instance, using the JavaScript fetch API as illustrated in this comment;

            Source https://stackoverflow.com/questions/68835360

            QUESTION

            transformers AutoTokenizer.tokenize introducing extra characters
            Asked 2021-Nov-13 at 06:48

            I am using HuggingFace transformers AutoTokenizer to tokenize small segments of text. However this tokenization is splitting incorrectly in the middle of words and introducing # characters to the tokens. I have tried several different models with the same results.

            Here is an example of a piece of text and the tokens that were created from it.

            ...

            ANSWER

            Answered 2021-Nov-13 at 06:48

            This is not an error but a feature. BERT and other transformers use WordPiece tokenization algorithm that tokenizes strings into either: (1) known words; or (2) "word pieces" for unknown words in the tokenizer vocabulary.

            In your examle, words "CTO", "TLR", and "Pty" are not in the tokenizer vocabulary, and thus WordPiece splits them into subwords. E.g. the first subword is "CT" and another part is "##O" where "##" denotes that the subword is connected to the predecessor.

            This is a great feature that allows to represent any string.

            Source https://stackoverflow.com/questions/69921629

            QUESTION

            Tokenizers change vocabulary entry
            Asked 2021-Nov-02 at 10:48

            I have some text which I want to perform NLP on. To do so, I download a pre-trained tokenizer like so:

            ...

            ANSWER

            Answered 2021-Nov-02 at 02:16

            If you can find distilbert folder in your pc, you can see vocabulary is basically txt file that contains only one column. You can do whatever you want to do.

            Source https://stackoverflow.com/questions/69780823

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

            Vulnerabilities

            No vulnerabilities reported

            Install Tokenizer

            You can download it from GitHub.
            You can use Tokenizer like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the Tokenizer component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .

            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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