KeyBERT
spaCy
KeyBERT | spaCy | |
---|---|---|
5 | 106 | |
3,217 | 28,789 | |
- | 0.6% | |
6.1 | 9.2 | |
about 2 months ago | 3 days ago | |
Python | Python | |
MIT License | MIT License |
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KeyBERT
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I want to extract important keywords from large documents...
Use something else like KeyBERT or BERTopic: https://github.com/MaartenGr/KeyBERT It's much faster.
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[D]: Predict the most probable document including the answer to a given question
Using keyword similarity using KeyBERT:https://github.com/MaartenGr/KeyBERT (i.e. loading keywords for each of the given documents and compare to the keywords of the question)
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BERT execution time
Would anyone know an equation or a general rule of thumb for how long it would take this BERT algorithm (KeyBERT: https://github.com/MaartenGr/KeyBERT) to select n keywords from a string of character length m on a GPU of certain relevant specs?
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[P] Building model to extract keywords from legal documents
Look into rake, pke, phrasemachine, pyate, keybert.
- Alternate approaches to TF-IDF?
spaCy
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Step by step guide to create customized chatbot by using spaCy (Python NLP library)
Hi Community, In this article, I will demonstrate below steps to create your own chatbot by using spaCy (spaCy is an open-source software library for advanced natural language processing, written in the programming languages Python and Cython):
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Best AI SEO Tools for NLP Content Optimization
SpaCy: An open-source library providing tools for advanced NLP tasks like tokenization, entity recognition, and part-of-speech tagging.
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Who has the best documentation you’ve seen or like in 2023
spaCy https://spacy.io/
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A beginner’s guide to sentiment analysis using OceanBase and spaCy
In this article, I'm going to walk through a sentiment analysis project from start to finish, using open-source Amazon product reviews. However, using the same approach, you can easily implement mass sentiment analysis on your own products. We'll explore an approach to sentiment analysis with one of the most popular Python NLP packages: spaCy.
- Retrieval Augmented Generation (RAG): How To Get AI Models Learn Your Data & Give You Answers
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Against LLM Maximalism
Spacy [0] is a state-of-art / easy-to-use NLP library from the pre-LLM era. This post is the Spacy founder's thoughts on how to integrate LLMs with the kind of problems that "traditional" NLP is used for right now. It's an advertisement for Prodigy [1], their paid tool for using LLMs to assist data labeling. That said, I think I largely agree with the premise, and it's worth reading the entire post.
The steps described in "LLM pragmatism" are basically what I see my data science friends doing — it's hard to justify the cost (money and latency) in using LLMs directly for all tasks, and even if you want to you'll need a baseline model to compare against, so why not use LLMs for dataset creation or augmentation in order to train a classic supervised model?
[0] https://spacy.io/
[1] https://prodi.gy/
- Swirl: An open-source search engine with LLMs and ChatGPT to provide all the answers you need 🌌
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How to predict this sequence?
spaCy
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What do you all think about (setq sentence-end-double-space nil)?
I chose spacy. Although it's not state of the art, it's very well established and stable.
- spaCy: Industrial-Strength Natural Language Processing
What are some alternatives?
yake - Single-document unsupervised keyword extraction
TextBlob - Simple, Pythonic, text processing--Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation, and more.
RAKE-tutorial - A python implementation of the Rapid Automatic Keyword Extraction
Stanza - Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages
flashtext - Extract Keywords from sentence or Replace keywords in sentences.
NLTK - NLTK Source
pke - Python Keyphrase Extraction module
BERT-NER - Pytorch-Named-Entity-Recognition-with-BERT
faiss - A library for efficient similarity search and clustering of dense vectors.
polyglot - Multilingual text (NLP) processing toolkit
scattertext - Beautiful visualizations of how language differs among document types.
textacy - NLP, before and after spaCy