Apple-M1-BERT | 3X speedup over Apple ’ s TensorFlow plugin
kandi X-RAY | Apple-M1-BERT Summary
kandi X-RAY | Apple-M1-BERT Summary
Apple-M1-BERT is a Python library. Apple-M1-BERT has no bugs, it has no vulnerabilities and it has low support. However Apple-M1-BERT build file is not available. You can download it from GitHub.
3X speedup over Apple’s TensorFlow plugin by using Apache TVM on M1
3X speedup over Apple’s TensorFlow plugin by using Apache TVM on M1
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Quality
Security
License
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Apple-M1-BERT has a low active ecosystem.
It has 120 star(s) with 7 fork(s). There are 52 watchers for this library.
It had no major release in the last 6 months.
There are 2 open issues and 0 have been closed. There are 1 open pull requests and 0 closed requests.
It has a neutral sentiment in the developer community.
The latest version of Apple-M1-BERT is current.
Quality
Apple-M1-BERT has 0 bugs and 0 code smells.
Security
Apple-M1-BERT has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
Apple-M1-BERT code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
Apple-M1-BERT 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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Apple-M1-BERT releases are not available. You will need to build from source code and install.
Apple-M1-BERT has no build file. You will be need to create the build yourself to build the component from source.
Installation instructions are not available. Examples and code snippets are available.
It has 436 lines of code, 16 functions and 10 files.
It has low code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA
kandi has reviewed Apple-M1-BERT and discovered the below as its top functions. This is intended to give you an instant insight into Apple-M1-BERT implemented functionality, and help decide if they suit your requirements.
- Run a tuner
- Load a model
- Convert keras to graphdef
- Measure a function over a given function
- Returns a keras model
- Load a keras model
- Save graphdef to file
Get all kandi verified functions for this library.
Apple-M1-BERT Key Features
No Key Features are available at this moment for Apple-M1-BERT.
Apple-M1-BERT Examples and Code Snippets
No Code Snippets are available at this moment for Apple-M1-BERT.
Community Discussions
No Community Discussions are available at this moment for Apple-M1-BERT.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install Apple-M1-BERT
You can download it from GitHub.
You can use Apple-M1-BERT 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 Apple-M1-BERT 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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