SudachiPy
Python version of Sudachi, a Japanese tokenizer. (by WorksApplications)
spaCy
💫 Industrial-strength Natural Language Processing (NLP) in Python (by explosion)
SudachiPy | spaCy | |
---|---|---|
3 | 107 | |
348 | 28,887 | |
- | 1.1% | |
1.6 | 9.2 | |
over 1 year ago | 4 days ago | |
Python | Python | |
Apache License 2.0 | 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.
SudachiPy
Posts with mentions or reviews of SudachiPy.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-09-01.
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Sakubun - a tool I made to help you practice kanji, with customized quiz questions and sentences
The current readings were generated with SudachiPy, with a little processing. UniDic seems pretty interesting, I'll check it out. Do you know how well its accuracy is, compared to Sudachi?
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software which turn hiragana and katakana into kanji
There are free tools for both of these things. I made game2text to do OCR and script matching. It includes a segmentation and normalization library Sudachi but I have not used its normalization feature for the app. I'm not sure anyone else even wants this feature but it will be pretty straightforward to add it if you're familiar with Python and vanilla Javascript.
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Tokenizing / picking words out of non-english languages
spaCy uses SudachiPy internally (see the doc comment about that), so if you don't need any of spaCy's extra features or want more control over the tokenization, you could use SudachiPy directly.
spaCy
Posts with mentions or reviews of spaCy.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-12-06.
- How I discovered Named Entity Recognition while trying to remove gibberish from a string.
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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.