xlnet_extension_tf | XLNet Extension in TensorFlow | Natural Language Processing library
kandi X-RAY | xlnet_extension_tf Summary
kandi X-RAY | xlnet_extension_tf Summary
xlnet_extension_tf is a Python library typically used in Artificial Intelligence, Natural Language Processing, Deep Learning, Tensorflow, Bert applications. xlnet_extension_tf has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However xlnet_extension_tf build file is not available. You can download it from GitHub.
XLNet Extension in TensorFlow
XLNet Extension in TensorFlow
Support
Quality
Security
License
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Support
xlnet_extension_tf has a low active ecosystem.
It has 115 star(s) with 24 fork(s). There are 5 watchers for this library.
It had no major release in the last 6 months.
There are 13 open issues and 7 have been closed. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of xlnet_extension_tf is current.
Quality
xlnet_extension_tf has 0 bugs and 0 code smells.
Security
xlnet_extension_tf has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
xlnet_extension_tf code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
xlnet_extension_tf is licensed under the Apache-2.0 License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.
Reuse
xlnet_extension_tf releases are not available. You will need to build from source code and install.
xlnet_extension_tf 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.
Top functions reviewed by kandi - BETA
kandi has reviewed xlnet_extension_tf and discovered the below as its top functions. This is intended to give you an instant insight into xlnet_extension_tf implemented functionality, and help decide if they suit your requirements.
- Evaluate validation function
- Displays the counter
- Given a list of refs leave out the left out of the refs
- Given a list of reference references return a list of reference references
- Return the model function for TPUEstimator
- Create a model
- Compute loss
- Process examples
- Write data to a json file
- Records prediction results
- Writes data to a json file
- Evaluate a ConLL file
- Make an ordered dict of scores
- Parse command line arguments
- Convert examples to features
- Build serving input function
- Convert a token file to a JSON file
- Convert a Coqa output file to output_file
- Evaluate predictions against the predicted labels
- Preprocessing preprocessing
- Get input function
- Convert a QUAC file to output_file
- Get input builder
- Save features as TFRecord
- Convert squad input file to JSON format
- Computes the best score for each prediction
- Run precision - recall curve
Get all kandi verified functions for this library.
xlnet_extension_tf Key Features
No Key Features are available at this moment for xlnet_extension_tf.
xlnet_extension_tf Examples and Code Snippets
No Code Snippets are available at this moment for xlnet_extension_tf.
Community Discussions
Trending Discussions on xlnet_extension_tf
QUESTION
No such file or directory Error with Google Cloud Storage
Asked 2020-Aug-27 at 01:21
I quite new to Google Cloud Platform and I am trying to train a model with TPU. I follow this tutorial to set up the TPU with Google Colab. All the code below follows the tutorial.
This is the step I have done:
...ANSWER
Answered 2020-Aug-08 at 04:12Can you post the part where run_coqa.py is opening the file?
It seems like you're trying to open it with a regular os. command where you should be using GCP's sdk.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install xlnet_extension_tf
You can download it from GitHub.
You can use xlnet_extension_tf 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 xlnet_extension_tf 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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