Bert_Classifier | SQL Database library
kandi X-RAY | Bert_Classifier Summary
kandi X-RAY | Bert_Classifier Summary
Bert_Classifier is a Python library typically used in Database, SQL Database, Keras, Bert, Neural Network applications. Bert_Classifier has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.
5、run_ChineseDailyNerCorpus.py 基于kashgari + bert/albert实现的ner. 9、uwsgi.py flask + uwsgi + keras部署深度学习模型预测接口.
5、run_ChineseDailyNerCorpus.py 基于kashgari + bert/albert实现的ner. 9、uwsgi.py flask + uwsgi + keras部署深度学习模型预测接口.
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Support
Bert_Classifier has a low active ecosystem.
It has 100 star(s) with 28 fork(s). There are 4 watchers for this library.
It had no major release in the last 6 months.
Bert_Classifier has no issues reported. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of Bert_Classifier is current.
Quality
Bert_Classifier has 0 bugs and 0 code smells.
Security
Bert_Classifier has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
Bert_Classifier code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
Bert_Classifier 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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Bert_Classifier 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.
Bert_Classifier saves you 1801 person hours of effort in developing the same functionality from scratch.
It has 4173 lines of code, 177 functions and 23 files.
It has high code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA
kandi has reviewed Bert_Classifier and discovered the below as its top functions. This is intended to give you an instant insight into Bert_Classifier implemented functionality, and help decide if they suit your requirements.
- Train model
- Build a tf TPUEstimator
- Builds a file - based input function
- Converts examples into features
- Truncate a sequence pair
- Convert a single example feature
- Translate string to number
- Convert a word to a number
- Convert a string to an integer
- Normalize time
- Convert a lunar calendar date to an integer
- Performs the forward computation
- Compute the differences between the given indices
- Predict class of text
- Reads the train examples
- Main function to download keywords
- Returns a list of input examples
- Convert a lunar date to an integer
- Read data file
- Load data from file
- Evaluate the validation function
- Evaluate the model
- Convert examples to features
- Returns the result of a function
- Parses a string
- Builds a model function for TPUEstimator
- Build a file - based input function
- Convert a solar date to lunar date
- Create a request from a raw text file
Get all kandi verified functions for this library.
Bert_Classifier Key Features
No Key Features are available at this moment for Bert_Classifier.
Bert_Classifier Examples and Code Snippets
No Code Snippets are available at this moment for Bert_Classifier.
Community Discussions
Trending Discussions on Bert_Classifier
QUESTION
Dimension does not match when using `keras.Model.fit` in `BERT` of tensorflow
Asked 2021-Mar-05 at 02:27
I follow the instruction of Fine-tuning BERT to build a model with my own dataset(It is kind of large, and greater than 20G), then take steps to re-cdoe my data and load them from tf_record files.
The training_dataset I create has the same signature as that in the instruction
ANSWER
Answered 2021-Mar-04 at 17:43They created the bert_classifier based on bert_config_file loaded from bert_config.json
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install Bert_Classifier
You can download it from GitHub.
You can use Bert_Classifier 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 Bert_Classifier 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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