abnet | Code for NeurIPS2020 "Incorporating BERT into Parallel Sequence Decoding with Adapters" | Machine Learning library

by lemmonation Python Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions(3)Vulnerabilities Install Support

kandi X-RAY | abnet Summary

abnet is a Python library typically used in Artificial Intelligence, Machine Learning, Bert applications. abnet has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

Code for NeurIPS2020 "Incorporating BERT into Parallel Sequence Decoding with Adapters"

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Quality

Security

License

Reuse

Support

abnet has a low active ecosystem.

It has 32 star(s) with 8 fork(s). There are 3 watchers for this library.

It had no major release in the last 6 months.

There are 3 open issues and 4 have been closed. On average issues are closed in 2 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of abnet is current.

Quality

abnet has no bugs reported.

Security

abnet has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

abnet 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

abnet releases are not available. You will need to build from source code and install.

Build file is available. You can 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 abnet and discovered the below as its top functions. This is intended to give you an instant insight into abnet implemented functionality, and help decide if they suit your requirements.

Main function
Add a word to the corpus
Train the model
Encodes a single line into integer ids
Adds two words
Create a mini - batch iterator
Generate the encoder from the given models
Returns the forward encoder
Forward decoder
Decode one token
Tokenize text
Generate a sample from a string
Load the checkpoint
Filters indices by size
Load a pre - trained model from a pre - trained model
Performs binarize
Perform forward attention
Compute all the gather list
Setup a registry
Forward computation
Forward a query
Generate softmax
Perform forward computation
Performs a single step
Generate a sentence pair
Creates a mini - batch iterator for the given dataset
Saves checkpoint
Train model

Get all kandi verified functions for this library.

abnet Key Features

No Key Features are available at this moment for abnet.

abnet Examples and Code Snippets

No Code Snippets are available at this moment for abnet.

Community Discussions

Trending Discussions on abnet

MySQL.Connector For Python Won't Update Values

AttributeError: 'tuple' object has no attribute 'encode' - MySQL.connector.Python

How to implement an efficient algorithm to search for a word in JSON?

QUESTION

MySQL.Connector For Python Won't Update Values

Asked 2020-Oct-27 at 22:24

What I am trying to do:

I want to run this function

...

ANSWER

Answered 2020-Oct-27 at 22:23

This coammnd is a simple string concatenation

Source https://stackoverflow.com/questions/64562798

QUESTION

AttributeError: 'tuple' object has no attribute 'encode' - MySQL.connector.Python

Asked 2020-Oct-26 at 20:56

Alrighty So this is the error

...

ANSWER

Answered 2020-Oct-26 at 20:56

Changing updaterScoren = "UPDATE bois SET pinkode_brugt = pinkode_brugt + 1 WHERE id = %s", (f,) to updaterScoren = "UPDATE bois SET pinkode_brugt = pinkode_brugt + 1 WHERE id = %s" % f
should do the job as you are using format variables incorrectly

Source https://stackoverflow.com/questions/64544765

QUESTION

How to implement an efficient algorithm to search for a word in JSON?

Asked 2018-Jul-02 at 09:35

I am trying to implement a word game, where a user types a letter on a board to form a meaningful word and submitt it, if the typed word is present in a JSON file, the user gets a point. So I have implemented the basics of the game, but unfortunately I have found that my linear algorithm is inefficient to traverse about 400k words in the JSON file. So my question is what kind of algorithm I can write to make it efficient? My interface looks like this. Letters appear randomly on the board.

A tiny part of my JSON file look like this

...

ANSWER

Answered 2018-Jul-02 at 09:35

You can sort the array in your database/json file alphabetically and then use a binary search algorithm to search for words efficiently.

An implementation of a binary search algorithm is defined below (source):

Source https://stackoverflow.com/questions/51132152

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

Vulnerabilities

No vulnerabilities reported

Install abnet

You can download it from GitHub.
You can use abnet 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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