transformer-xl | Music and text generation with Transformer-XL | Translation library

by davidsvy Python Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | transformer-xl Summary

transformer-xl is a Python library typically used in Utilities, Translation, Deep Learning, Tensorflow, Neural Network, Transformer applications. transformer-xl has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However transformer-xl build file is not available. You can download it from GitHub.

The goal of this project is to generate long and coherent sequences of data using Transformer architectures based on the following papers:. The neural networks are tested on two separate tasks : music generation and text generation. All the models are implemented from scratch in Tensorflow 2.

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Security

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Support

transformer-xl has a low active ecosystem.

It has 28 star(s) with 6 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 3 have been closed. On average issues are closed in 19 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of transformer-xl is current.

Quality

transformer-xl has no bugs reported.

Security

transformer-xl has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

transformer-xl is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

transformer-xl releases are not available. You will need to build from source code and install.

transformer-xl has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions are not available. Examples and code snippets are available.

Top functions reviewed by kandi - BETA

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

Preprocess an email
Fix punctuation
Mask email addresses
Return the email body of the given string
Call the model
Compute lookahead mask
Get the next memory
Preprocess a dataset
Split a string into email addresses
Preprocess a corpus
Generate the MIDis computation
Softmax function
Convert features to a MIDI track
Load a tf Dataset
Load features from file
Convert features to text
Fills missing masks
Build a MIDI parser from a configuration
Build a Scam parser from a config
Builds a GatedTransformer from a given configuration
Calculates the time
Shuffle ragged_tensors
Build a Transformer from a given config
Generate text
Convert inputs to labels

Get all kandi verified functions for this library.

transformer-xl Key Features

No Key Features are available at this moment for transformer-xl.

transformer-xl Examples and Code Snippets

No Code Snippets are available at this moment for transformer-xl.

Community Discussions

Trending Discussions on transformer-xl

Getting PyCharm to find dependencies under

QUESTION

Getting PyCharm to find dependencies under

Asked 2019-Jul-09 at 19:22

Is there some way to tell PyCharm where to look for files?

Here's an example, I clone this repo, cd into transformer-xl/pytorch and run train.py and it works because utils is in . which Python interpreter includes in it's list of places it searches for imports.

However, when I open this project in PyCharm, it underlines all instances of utils, is there some way to fix this?

...

ANSWER

Answered 2019-Apr-22 at 10:02

Yes there is. You can define folders of a project as a source:

Source https://stackoverflow.com/questions/55718533

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

Vulnerabilities

No vulnerabilities reported

Install transformer-xl

You can download it from GitHub.
You can use transformer-xl 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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