MMT-Delib | Clone of the repository https : //github

by ImperialNLP Python Version: Current License: No License

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

kandi X-RAY | MMT-Delib Summary

MMT-Delib is a Python library. MMT-Delib has no bugs, it has no vulnerabilities and it has low support. However MMT-Delib build file is not available. You can download it from GitHub.

Clone of the repository

Support

Quality

Security

License

Reuse

Support

MMT-Delib has a low active ecosystem.

It has 8 star(s) with 2 fork(s). There are 6 watchers for this library.

It had no major release in the last 6 months.

MMT-Delib has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of MMT-Delib is current.

Quality

MMT-Delib has no bugs reported.

Security

MMT-Delib has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

MMT-Delib does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

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

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

Perform beam search
Get the shape of a tensor
Reshapes the beam dimension
Convert tensor to beam size
Defines a model function
Evaluate autoregressive model
Remove None values from a dictionary
Logs the sizes of each variable
Local mixture of experts
Input pipeline
Decompress seqcnn
Compresses data files
Distributed mixture of experts
Decodes from a file
Generate generator
Self attention
Memory - self - self - attention
Build input_fn
Calculate multihead attention
Reduce a multihead attention layer
A block of reversible residuals
Build a subtoken from a list of tokens
Performs prediction from a dataset
Attention between source and target
Constructs a memory - efficient convolutional memory
Dense dot product attention

Get all kandi verified functions for this library.

MMT-Delib Key Features

No Key Features are available at this moment for MMT-Delib.

MMT-Delib Examples and Code Snippets

No Code Snippets are available at this moment for MMT-Delib.

Community Discussions

No Community Discussions are available at this moment for MMT-Delib.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install MMT-Delib

You can download it from GitHub.
You can use MMT-Delib 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 .

Find more information at: