VLGrammar | Data can be downloaded here

by evelinehong Python Version: Current License: No License

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

kandi X-RAY | VLGrammar Summary

VLGrammar is a Python library. VLGrammar has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.

Data can be downloaded here.

Support

Quality

Security

License

Reuse

Support

VLGrammar has a low active ecosystem.

It has 8 star(s) with 1 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

VLGrammar has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of VLGrammar is current.

Quality

VLGrammar has no bugs reported.

Security

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

License

VLGrammar 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

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

Validate the parser
Update the statistics
Evaluate the data
Save the features to a device
Forward computation
Gets the actions from the given tree
Calculate F1 score
Return the normalized norm of all parameters
Return a model instance for the given data
Performs the auction search
Scans train_loader
Computes predictions for a given model
Calculate the root probability of x
Calculate the root probability of each embedding
Get train transform
Create a config dictionary
Evaluate the Hungarian model
Compute the weights for weakly augmenting
Calculate the log - likelihood
Get the topk features from the prediction
Train a model
Perform self - label training
Forward computation
Get train dataset
Compute the similarity between anchors
Create a torch optimizer for the given model

Get all kandi verified functions for this library.

VLGrammar Key Features

No Key Features are available at this moment for VLGrammar.

VLGrammar Examples and Code Snippets

No Code Snippets are available at this moment for VLGrammar.

Community Discussions

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

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

Vulnerabilities

No vulnerabilities reported

Install VLGrammar

You can download it from GitHub.
You can use VLGrammar 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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