Bert-Chinese-Text-Classification-Pytorch | Chinese text classification using Bert , ERNIE

by 649453932 Python Version: Current License: MIT

X-Ray Key Features Code Snippets(3)Community Discussions Vulnerabilities Install Support

kandi X-RAY | Bert-Chinese-Text-Classification-Pytorch Summary

Bert-Chinese-Text-Classification-Pytorch is a Python library. Bert-Chinese-Text-Classification-Pytorch has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. However Bert-Chinese-Text-Classification-Pytorch build file is not available. You can download it from GitHub.

Chinese text classification using Bert, ERNIE

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Quality

Security

License

Reuse

Support

Bert-Chinese-Text-Classification-Pytorch has a medium active ecosystem.

It has 3096 star(s) with 789 fork(s). There are 20 watchers for this library.

It had no major release in the last 6 months.

There are 125 open issues and 40 have been closed. On average issues are closed in 52 days. There are 3 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of Bert-Chinese-Text-Classification-Pytorch is current.

Quality

Bert-Chinese-Text-Classification-Pytorch has 0 bugs and 0 code smells.

Security

Bert-Chinese-Text-Classification-Pytorch has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

Bert-Chinese-Text-Classification-Pytorch code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

Bert-Chinese-Text-Classification-Pytorch is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

Bert-Chinese-Text-Classification-Pytorch releases are not available. You will need to build from source code and install.

Bert-Chinese-Text-Classification-Pytorch 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.

Bert-Chinese-Text-Classification-Pytorch saves you 2285 person hours of effort in developing the same functionality from scratch.

It has 4993 lines of code, 349 functions and 27 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed Bert-Chinese-Text-Classification-Pytorch and discovered the below as its top functions. This is intended to give you an instant insight into Bert-Chinese-Text-Classification-Pytorch implemented functionality, and help decide if they suit your requirements.

Create a trained model from a pretrained model
Loads weights from a TensorFlow checkpoint file
Construct an instance from a JSON file
Load a pre - trained model from a pretrained model
Load tf weights in OpenAI checkpoint folder
Create an instance from a json file
Train the model
Returns a timedelta from start_time to end_time
Forward computation
Compute the logit
Create a model from a pretrained model
Load weights from a tf gpt2 checkpoint file
Get learning rate multiplier
Forward layer
Convert OpenAI checkpoint to PyTorch model
Compute the attention
Convert TF checkpoint to PyTorch model
Get the time in seconds from start_time
Convert a GPT2 checkpoint file to PyTorch model
Converts a TensorFlow checkpoint file to a pytorch dataset
Compute the attention matrix
Build a dataset
Performs the forward computation
Load a pre - trained model from a pre - trained model
Tokenize text
Computes log probability for each cluster
Load a pretrained model from a pretrained model

Get all kandi verified functions for this library.

Bert-Chinese-Text-Classification-Pytorch Key Features

No Key Features are available at this moment for Bert-Chinese-Text-Classification-Pytorch.

Bert-Chinese-Text-Classification-Pytorch Examples and Code Snippets

BERT,Fine-tuning with BERT,Sentence (and sentence-pair) classification tasks

Python

Lines of Code : 34

License : Permissive (Apache-2.0)

Copy

export BERT_BASE_DIR=/path/to/bert/uncased_L-12_H-768_A-12
export GLUE_DIR=/path/to/glue

python run_classifier.py \
  --task_name=MRPC \
  --do_train=true \
  --do_eval=true \
  --data_dir=$GLUE_DIR/MRPC \
  --vocab_file=$BERT_BASE_DIR/vocab.txt \

BERT,Fine-tuning with BERT,Sentence (and sentence-pair) classification tasks

Python

Lines of Code : 34

License : Permissive (Apache-2.0)

Copy

export BERT_BASE_DIR=/path/to/bert/uncased_L-12_H-768_A-12
export GLUE_DIR=/path/to/glue

python run_classifier.py \
  --task_name=MRPC \
  --do_train=true \
  --do_eval=true \
  --data_dir=$GLUE_DIR/MRPC \
  --vocab_file=$BERT_BASE_DIR/vocab.txt \

BERT,Fine-tuning with BERT,Sentence (and sentence-pair) classification tasks

Python

Lines of Code : 34

License : Permissive (Apache-2.0)

Copy

export BERT_BASE_DIR=/path/to/bert/uncased_L-12_H-768_A-12
export GLUE_DIR=/path/to/glue

python run_classifier.py \
  --task_name=MRPC \
  --do_train=true \
  --do_eval=true \
  --data_dir=$GLUE_DIR/MRPC \
  --vocab_file=$BERT_BASE_DIR/vocab.txt \

Community Discussions

No Community Discussions are available at this moment for Bert-Chinese-Text-Classification-Pytorch.Refer to stack overflow page for discussions.

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install Bert-Chinese-Text-Classification-Pytorch

You can download it from GitHub.
You can use Bert-Chinese-Text-Classification-Pytorch 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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