pysimilar VS pronomial

Compare pysimilar vs pronomial and see what are their differences.

pysimilar

A python library for computing the similarity between two strings (text) based on cosine similarity (by Kalebu)
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pysimilar pronomial
1 1
19 0
- -
0.0 0.0
almost 2 years ago about 2 years ago
Python Python
MIT License Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

pysimilar

Posts with mentions or reviews of pysimilar. We have used some of these posts to build our list of alternatives and similar projects.

pronomial

Posts with mentions or reviews of pronomial. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing pysimilar and pronomial you can also consider the following projects:

bert - TensorFlow code and pre-trained models for BERT

gum - A tool for glamorous shell scripts 🎀

spokestack-python - Spokestack is a library that allows a user to easily incorporate a voice interface into any Python application with a focus on embedded systems.

gluon-nlp - NLP made easy

clip-as-service - 🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP

learn - Neuro-symbolic interpretation learning (mostly just language-learning, for now)

mycroft-core - Mycroft Core, the Mycroft Artificial Intelligence platform.

unisim - UniSim is a package for efficient similarity computation, fuzzy matching, and clustering of data.

pronounTryouts.sh - Mad libs but with name and pronouns. Enjoy.

coref - BERT for Coreference Resolution

OpenPrompt - An Open-Source Framework for Prompt-Learning.