ccks_triple_extract | 限定领域的三元组抽取的一次尝试,本文将会介绍笔者在2019语言与智能技术竞赛的三元组抽取比赛方面的一次尝试。
kandi X-RAY | ccks_triple_extract Summary
kandi X-RAY | ccks_triple_extract Summary
ccks_triple_extract is a Python library. ccks_triple_extract has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.
限定领域的三元组抽取的一次尝试,本文将会介绍笔者在2019语言与智能技术竞赛的三元组抽取比赛方面的一次尝试。
限定领域的三元组抽取的一次尝试,本文将会介绍笔者在2019语言与智能技术竞赛的三元组抽取比赛方面的一次尝试。
Support
Quality
Security
License
Reuse
Support
ccks_triple_extract has a low active ecosystem.
It has 97 star(s) with 23 fork(s). There are 4 watchers for this library.
It had no major release in the last 6 months.
There are 3 open issues and 1 have been closed. On average issues are closed in 12 days. There are 1 open pull requests and 0 closed requests.
It has a neutral sentiment in the developer community.
The latest version of ccks_triple_extract is current.
Quality
ccks_triple_extract has 0 bugs and 72 code smells.
Security
ccks_triple_extract has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
ccks_triple_extract code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
ccks_triple_extract 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
ccks_triple_extract 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.
ccks_triple_extract saves you 1871 person hours of effort in developing the same functionality from scratch.
It has 4127 lines of code, 201 functions and 32 files.
It has high code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA
kandi has reviewed ccks_triple_extract and discovered the below as its top functions. This is intended to give you an instant insight into ccks_triple_extract implemented functionality, and help decide if they suit your requirements.
- R Prelln_transformer model
- Get the shape of a tensor
- Assert that the tensor is equal to the expected rank
- Reshape a tensor
- Build a function for TPUEstimator
- Get the assignment map from a checkpoint
- Create an optimizer
- Apply gradients
- Embed word embedding
- Builds a file - like input function
- Create TrainingInstances
- Add bio list to bio
- Creates attention_mask_from_tensor
- Convert examples to features
- Generate a sequence mask
- Extract entity from a tag
- Load data from a file
- Train model
- Check if the case matches the given checkpoint
- Embedding postprocessor
- Create MLM instances from the original document
- Optimize the graph
- Write examples to examples
- Build input function
- Create a tf TPU
- Tokenize text
Get all kandi verified functions for this library.
ccks_triple_extract Key Features
No Key Features are available at this moment for ccks_triple_extract.
ccks_triple_extract Examples and Code Snippets
No Code Snippets are available at this moment for ccks_triple_extract.
Community Discussions
No Community Discussions are available at this moment for ccks_triple_extract.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install ccks_triple_extract
You can download it from GitHub.
You can use ccks_triple_extract 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 ccks_triple_extract 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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