BERT-NER | Use Google 's BERT for named entity recognition （CoNLL-2003 | Natural Language Processing library

by kyzhouhzau Python Version: Current License: MIT

X-Ray Key Features Code Snippets(3)Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | BERT-NER Summary

BERT-NER is a Python library typically used in Artificial Intelligence, Natural Language Processing, Tensorflow, Bert, Transformer applications. BERT-NER has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. However BERT-NER build file is not available. You can download it from GitHub.

Use Google's BERT for named entity recognition （CoNLL-2003 as the dataset）.

Support

Quality

Security

License

Reuse

Support

BERT-NER has a medium active ecosystem.

It has 1176 star(s) with 342 fork(s). There are 37 watchers for this library.

It had no major release in the last 6 months.

There are 71 open issues and 19 have been closed. On average issues are closed in 64 days. There are 7 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of BERT-NER is current.

Quality

BERT-NER has 0 bugs and 0 code smells.

Security

BERT-NER has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

BERT-NER code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

BERT-NER 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-NER releases are not available. You will need to build from source code and install.

BERT-NER 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 BERT-NER and discovered the below as its top functions. This is intended to give you an instant insight into BERT-NER implemented functionality, and help decide if they suit your requirements.

Main function .
Convert a single example .
Build a function that builds the model .
Calculate confusion matrix from confusion matrix .
Compute the confusion matrix .
Creates a new metric variable .
Compute the fbeta function for predictions .
Calculate recall .
Calculate precision for confusion matrix classification .
Builds a tf . input_fn .

Get all kandi verified functions for this library.

BERT-NER Key Features

No Key Features are available at this moment for BERT-NER.

BERT-NER Examples and Code Snippets

Keras-Bert-Ner,Train Phase

Python

Lines of Code : 87

License : Permissive (MIT)

Copy

[
    [
        "揭秘趣步骗局，趣步是什么，趣步是怎么赚钱的？趣步公司可靠吗？趣步合法吗？相信是众多小伙伴最关心的话题，今天小编就来给大家揭开趣步这面“丑恶”且神秘的面纱，让小伙伴们看清事情的真相。接下来，我用简单的文字，给大家详细剖析一下趣步公司及趣步app的逻辑到底是什么样>的？3分钟时间...全文：?揭秘趣步骗局，趣步是什么，趣步是怎么赚钱的？趣步公司可靠吗？趣步合法吗？相信是众多小伙伴最关心的话题，今天小编就来给大家揭开趣步这面“丑恶”且神秘的面纱，让小伙伴们看清事

Keras-Bert-Ner,Training,Parameters

Python

Lines of Code : 79

License : Permissive (MIT)

Copy

(nlp) liushaoweihua@ai-server-6:~/jupyterlab/Keras-Bert-Ner$ python keras_bert_ner/train/help.py --help
usage: help.py [-h] -train_data TRAIN_DATA [-dev_data DEV_DATA]
               [-save_path SAVE_PATH] [-albert] -bert_config BERT_CONFIG

Keras-Bert-Ner,Training,Example

Python

Lines of Code : 55

License : Permissive (MIT)

Copy

PRETRAINED_LM_DIR="/home1/liushaoweihua/pretrained_lm/albert_tiny_250k" # your pretrained language model path
DATA_DIR="../data" # your train/dev data path
OUTPUT_DIR="../models" # where to store the NER model

python run_train.py \
    -train_data=$

Community Discussions

Trending Discussions on BERT-NER

Python logger format broken: I0716 instead of INFO

Tensorflow _tpu_ops.so not found while using GPU

QUESTION

Python logger format broken: I0716 instead of INFO

Asked 2019-Jul-18 at 12:39

By some reason python logger format sometimes kinda broken. I'm not sure what's wrong, looks like encoding issue:

...

ANSWER

Answered 2019-Jul-18 at 12:39

Python API

If you just want to customize tensorflows logging format, replace the formatter in absl and tensorflow loggers:

Source https://stackoverflow.com/questions/57065036

QUESTION

Tensorflow _tpu_ops.so not found while using GPU

Asked 2019-Mar-24 at 15:31

I ported this BERT NER github code to google colab, where I manually set the flags to run it (https://github.com/kyzhouhzau/BERT-NER).

I set use_tpu to False, so it should be using GPU.

flags.DEFINE_bool("use_tpu", False, "Whether to use TPU or GPU/CPU.")

The TF version used on colab is 1.13.1 and the command tf.test.gpu_device_name() returns '/device:GPU:0'.

This is the error message that I get when running tf.app.run(). Is this failing because it's looking for a TPU? How can I fix it? Thanks for your help!

...

ANSWER

Answered 2019-Mar-24 at 15:31

I figured it out. When I was downloading the tf_metrics library from https://github.com/guillaumegenthial/tf_metrics.git using !pip install git+https://github.com/guillaumegenthial/tf_metrics.git, it somehow re-installed tensorflow-gpu and my guess is that it corrupted it.

I downloaded tf_metrics.py separately instead and it's now working on google colab.

Source https://stackoverflow.com/questions/55307840

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

Vulnerabilities

No vulnerabilities reported

Install BERT-NER

You can download it from GitHub.
You can use BERT-NER 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 .

Find more information at: