spacy-sentence-bert | Sentence transformers models for SpaCy | Natural Language Processing library

by MartinoMensio Python Version: 0.1.2 License: MIT

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

kandi X-RAY | spacy-sentence-bert Summary

spacy-sentence-bert is a Python library typically used in Artificial Intelligence, Natural Language Processing, Bert, Transformer applications. spacy-sentence-bert has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install spacy-sentence-bert' or download it from GitHub, PyPI.

Sentence transformers models for SpaCy

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Quality

Security

License

Reuse

Support

spacy-sentence-bert has a low active ecosystem.

It has 77 star(s) with 4 fork(s). There are 2 watchers for this library.

It had no major release in the last 12 months.

There are 2 open issues and 2 have been closed. On average issues are closed in 346 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of spacy-sentence-bert is 0.1.2

Quality

spacy-sentence-bert has 0 bugs and 1 code smells.

Security

spacy-sentence-bert has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

spacy-sentence-bert code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

spacy-sentence-bert 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

spacy-sentence-bert releases are available to install and integrate.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

It has 329 lines of code, 17 functions and 7 files.

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

Top functions reviewed by kandi - BETA

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

Creates a new language model
Create a new NLP
Return the vector representation of a sentence
Get a model by its name
Create a Doc from a given bytes object
Set user hooks
Setup the package
Create a SentenceBert from a given NLP

Get all kandi verified functions for this library.

spacy-sentence-bert Key Features

No Key Features are available at this moment for spacy-sentence-bert.

spacy-sentence-bert Examples and Code Snippets

Sentence-BERT for spaCy,Usage,nlp.add_pipe

Python

Lines of Code : 13

License : Permissive (MIT)

Copy

import spacy
nlp = spacy.blank('en')
nlp.add_pipe('sentence_bert', config={'model_name': 'allenai-specter'})
nlp.pipe_names

# get two documents
doc_1 = nlp('Hi there, how are you?')
doc_2 = nlp('Hello there, how are you doing today?')
# get the vect

Sentence-BERT for spaCy,Utils

Python

Lines of Code : 7

License : Permissive (MIT)

Copy

VERSION=0.1.2
# build the standalone models (17)
./build_models.sh
# build the archive at dist/spacy_sentence_bert-${VERSION}.tar.gz
python setup.py sdist
# upload to pypi
twine upload dist/spacy_sentence_bert-${VERSION}.tar.gz

Sentence-BERT for spaCy,Usage,spacy.load

Python

Lines of Code : 2

License : Permissive (MIT)

Copy

import spacy
nlp = spacy.load('en_stsb_roberta_large')

Community Discussions

Trending Discussions on spacy-sentence-bert

AttributeError: type object 'Language' has no attribute 'factory'

How to find the similarity of sentences in 2 columns of a dataframe using spacy

QUESTION

AttributeError: type object 'Language' has no attribute 'factory'

Asked 2021-Nov-08 at 15:23

I am getting error while using "spacy_sentence_bert"

Code:

...

ANSWER

Answered 2021-Jul-26 at 17:40

The issue seems to be with your environment.

AttributeError: type object 'Language' has no attribute 'factory' message

is a spacy 2.x error.

Please try to run it with spacy 3.x. If you have already installed 3.x, then please verify if your virtual environment is pointing to correct python.

Source https://stackoverflow.com/questions/68533685

QUESTION

How to find the similarity of sentences in 2 columns of a dataframe using spacy

Asked 2021-Oct-09 at 05:18

I pulled this code from https://spacy.io/universe/project/spacy-sentence-bert

...

ANSWER

Answered 2021-Oct-09 at 05:18

I assume that your first row consists of headers, the data will start from the next row after header, and also assume that you are using panda to convert csv to dataframe, the below code works in my environment.

Source https://stackoverflow.com/questions/69443805

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

Vulnerabilities

No vulnerabilities reported

Install spacy-sentence-bert

To install this package, you can run one of the following:. You can install standalone spaCy packages from GitHub with pip. If you install standalone packages, you will be able to load a language model directly by using the spacy.load API, without need to add a pipeline stage. This table takes the models listed on the Sentence Transformers documentation and shows some statistics along with the instruction to install the standalone models. If you don't want to install the standalone models, you can still use them by adding a pipeline stage (see below). If your model is not in this list (e.g., xlm-r-base-en-ko-nli-ststb), you can still use it with this library but not as a standalone language. You will need to add a pipeline stage properly configured (see below the nlp.add_pipe API).
spaCy>=3.0.0,<4.0.0, tested on version 3.0.3
sentence-transformers: tested on version 0.1.4
pip install spacy_sentence_bert
pip install git+https://github.com/MartinoMensio/spacy-sentence-bert.git

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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