NLP-Model-for-Corpus-Similarity
A NLP algorithm I developed to determine the similarity or relation between two documents/Wikipedia articles. Inspired by the cosine similarity algorithm and built from WordNet. (by kohjiaxuan)
bart-base-jax
JAX implementation of the bart-base model (by ayaka14732)
| NLP-Model-for-Corpus-Similarity | bart-base-jax | |
|---|---|---|
| 1 | 1 | |
| 9 | 29 | |
| - | - | |
| 0.0 | 1.4 | |
| almost 5 years ago | almost 2 years ago | |
| Python | Python | |
| MIT License | - |
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.
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.
NLP-Model-for-Corpus-Similarity
Posts with mentions or reviews of NLP-Model-for-Corpus-Similarity.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-02-24.
bart-base-jax
Posts with mentions or reviews of bart-base-jax.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-10-21.
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How we created an in-browser BERT attention visualiser without a server - TrAVis: Transformer Attention Visualiser
Firstly, we implemented the BART model from scratch using JAX. We chose JAX because it is an amazing deep learning framework that enables us to write clear source code, and it can be easily converted to NumPy, which can be executed in-browser. We chose the #BART model because it is a complete encoder-decoder model, so it can be easily adapted to other models, such as BERT, by simply taking a subset of the source code.
What are some alternatives?
When comparing NLP-Model-for-Corpus-Similarity and bart-base-jax you can also consider the following projects:
StringDistances.jl - String Distances in Julia
TrAVis - TrAVis: Visualise BERT attention in your browser
Probabilistic-Programming-and-Bayesian-Methods-for-Hackers - aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
word-piece-tokenizer - A Lightweight Word Piece Tokenizer
wordview - A Python package for Exploratory Data Analysis (EDA) for text-based data.
d3 - Bring data to life with SVG, Canvas and HTML. :bar_chart::chart_with_upwards_trend::tada: