KoELECTRA | Pretrained ELECTRA Model for Korean | Natural Language Processing library

by monologg Python Version: Current License: Apache-2.0

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

kandi X-RAY | KoELECTRA Summary

KoELECTRA is a Python library typically used in Artificial Intelligence, Natural Language Processing, Deep Learning, Pytorch, Tensorflow, Bert, Neural Network, Transformer applications. KoELECTRA has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However KoELECTRA build file is not available. You can download it from GitHub.

Pretrained ELECTRA Model for Korean

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Quality

Security

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KoELECTRA has a low active ecosystem.

It has 537 star(s) with 137 fork(s). There are 11 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 25 have been closed. On average issues are closed in 15 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of KoELECTRA is current.

Quality

KoELECTRA has 0 bugs and 0 code smells.

Security

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

KoELECTRA code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

KoELECTRA 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.

Reuse

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

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

Installation instructions, examples and code snippets are available.

KoELECTRA saves you 2996 person hours of effort in developing the same functionality from scratch.

It has 6525 lines of code, 447 functions and 45 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

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

Train the model
Evaluate a model
Load and cache examples
Compute the metrics for a given task
Calculate the maximum accuracy of a prediction
Feature the given example
Check if the word spans in the document spans
Improve the answer span
Transformer transformer
Attention layer
Tokenize text
Returns a pretraining function
Gets the masked lm output
Create pretraining
Write tf examples
Compute the F1 score
Create an optimizer
Create attention_mask_from_tensor
Get the discriminator output
Get the prediction module
Lookup word embedding
Build the prediction module
Embedding postprocessor
Fits the given example
Load examples and cache them
Run Finetuning
Mask the inputs

Get all kandi verified functions for this library.

KoELECTRA Key Features

No Key Features are available at this moment for KoELECTRA.

KoELECTRA Examples and Code Snippets

No Code Snippets are available at this moment for KoELECTRA.

Community Discussions

Trending Discussions on KoELECTRA

An error occurs when predict with the same data as when performing train (expects 3 input(s), but it received 75 input tensors.)

QUESTION

An error occurs when predict with the same data as when performing train (expects 3 input(s), but it received 75 input tensors.)

Asked 2021-Jan-08 at 07:42

After training the model, I tried to make predictions, but an error occurred and I don't know how to fix it.

The model was constructed using electra.

here is my model

...

ANSWER

Answered 2021-Jan-08 at 07:42

It was a tensor dimension problem.

Source https://stackoverflow.com/questions/65517232

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

Vulnerabilities

No vulnerabilities reported

Install KoELECTRA

You can download it from GitHub.
You can use KoELECTRA 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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