embedding-for-textual-entailment
kandi X-RAY | embedding-for-textual-entailment Summary
kandi X-RAY | embedding-for-textual-entailment Summary
embedding-for-textual-entailment is a Python library. embedding-for-textual-entailment has no bugs, it has no vulnerabilities and it has low support. However embedding-for-textual-entailment build file is not available. You can download it from GitHub.
embedding-for-textual-entailment
embedding-for-textual-entailment
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Support
embedding-for-textual-entailment has a low active ecosystem.
It has 6 star(s) with 1 fork(s). There are 1 watchers for this library.
It had no major release in the last 6 months.
embedding-for-textual-entailment has no issues reported. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of embedding-for-textual-entailment is current.
Quality
embedding-for-textual-entailment has no bugs reported.
Security
embedding-for-textual-entailment has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
embedding-for-textual-entailment 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
embedding-for-textual-entailment releases are not available. You will need to build from source code and install.
embedding-for-textual-entailment 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 embedding-for-textual-entailment and discovered the below as its top functions. This is intended to give you an instant insight into embedding-for-textual-entailment implemented functionality, and help decide if they suit your requirements.
- Train the model
- Return dictionary of parameters to save
- Print prediction
- Saves model parameters to dirname
- Expiral experiment
- Compute shared shared dataset
- Compute the gradient of the gradients
- Predicts embedding
- Compute intra attention
- Compute the composition of a sentence
- Computes the similarity between two sentences
- Concatenate a word network
- Projects the given embeddings
- Find frequent SNLI
- Clear out labels
- Loads a trained model
- Load w2v file
- Performs LSTM attention
- Load data from file
- Attention function
- Aggregate the network
- Load SICKTV txt
- Evaluate Rte
- Reads an SNLI corpus
- Load embeddings
- Compute the similarity between two sentences
Get all kandi verified functions for this library.
embedding-for-textual-entailment Key Features
No Key Features are available at this moment for embedding-for-textual-entailment.
embedding-for-textual-entailment Examples and Code Snippets
No Code Snippets are available at this moment for embedding-for-textual-entailment.
Community Discussions
No Community Discussions are available at this moment for embedding-for-textual-entailment.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install embedding-for-textual-entailment
You can download it from GitHub.
You can use embedding-for-textual-entailment 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 embedding-for-textual-entailment 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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