RelationDectection | Sentence Embedding Alignment for Lifelong Relation
kandi X-RAY | RelationDectection Summary
kandi X-RAY | RelationDectection Summary
RelationDectection is a Python library. RelationDectection has no bugs, it has no vulnerabilities and it has low support. However RelationDectection build file is not available. You can download it from GitHub.
I put the code for the paper of "Sentence Embedding Alignment for Lifelong Relation Extraction" in this repo
I put the code for the paper of "Sentence Embedding Alignment for Lifelong Relation Extraction" in this repo
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Support
RelationDectection has a low active ecosystem.
It has 4 star(s) with 1 fork(s). There are no watchers for this library.
It had no major release in the last 6 months.
RelationDectection has no issues reported. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of RelationDectection is current.
Quality
RelationDectection has no bugs reported.
Security
RelationDectection has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
RelationDectection 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.
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RelationDectection releases are not available. You will need to build from source code and install.
RelationDectection has no build file. You will be need to create the build yourself to build the component from source.
Top functions reviewed by kandi - BETA
kandi has reviewed RelationDectection and discovered the below as its top functions. This is intended to give you an instant insight into RelationDectection implemented functionality, and help decide if they suit your requirements.
- Run the model
- Rank a sentence
- Compute queue embedding
- Compute question embedding
- Generate training data
- Split a relation into words
- Clean a list of relations
- Build vocabulary embedding
- Read model embedding file
- Select sample data based on categorical data
- Calculate the weight for the current model
- Print the average results
- Select samples from the queued embedding
- Mix random centers
- Generate a vocabulary
- Removes unseen relations from a sample
- Read relation names from a file
- Return a list of nearest training data points
- Compute the rel embedding of the training data
- Compute the relation embedding for each relation
- Compute the cos similarity between two embeds
- This function expands the relation graph
- Performs k - means clustering
- Gets gradients from memory
- This method updates the reverse model
- Visualize the PCA
Get all kandi verified functions for this library.
RelationDectection Key Features
No Key Features are available at this moment for RelationDectection.
RelationDectection Examples and Code Snippets
No Code Snippets are available at this moment for RelationDectection.
Community Discussions
No Community Discussions are available at this moment for RelationDectection.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install RelationDectection
You can download it from GitHub.
You can use RelationDectection 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.
You can use RelationDectection 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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