wink-eng-lite-model
wink-nlp
Our great sponsors
wink-eng-lite-model | wink-nlp | |
---|---|---|
5 | 21 | |
10 | 1,143 | |
- | 1.7% | |
0.0 | 8.1 | |
almost 3 years ago | 17 days ago | |
JavaScript | ||
MIT License | MIT License |
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.
wink-eng-lite-model
- SuperCharge Input Field for a Dictionary Website
-
How to run NLP on a PDF file?
winkNLP’s English language lite model uses a pre-trained state machine to recognize named entities.
-
How to tokenize a string?
To tokenize a string using winkNLP, read the text using readDoc. Then use the tokens method to extract a collection of tokens from the string. Follow this with the out method to get this collection as a JavaScript array. This is how you can tokenize a string:
-
How to do sentiment analysis?
winkNLP's English language lite model uses ML-SentiCon as a base with further training. For emojis it uses the Emoji Sentiment Ranking. Together, they deliver an f-score of about 84.5%.
-
How to find date and time in text?
Raw texts may contain many named entities like time, money, and hashtags. The English language lite model for winkNLP finds entities spanning multiple tokens by employing pre-trained finite state machine.
wink-nlp
-
Show HN: Next-token prediction in JavaScript – build fast LLMs from scratch
This is awesome, thanks. I've been messing with wink's NLP library (https://winkjs.org/wink-nlp/) to transform user queries and format responses so I can make a proper chat bot - will see what I can learn from these!
- Show HN: WinkNLP introduces key sentence extraction
- WinkNLP's recent feature — key sentence extraction delivers a performance of over 450,000 tokens/second or 1500 sentences/second on Apple M1/16GB
-
How to visualize timeline of a Wiki article?
Automatic generation of the timeline — a graphical representation of a time period, on which important events are marked — from a Wikipedia article is a fascinating idea and very useful in quickly grasping the historical perspective. This post outlines the approach to create a well formatted timeline from any Wikipedia article using WinkNLP’s API and Named Entity Recognition (NER) feature:
- WinkNLP delivers 600k tokens/second speed on browsers (MBP M1)
-
Hacker News top posts: Nov 24, 2022
Show HN: WinkNLP delivers 600k tokens/second speed on browsers\ (2 comments)
- Show HN: WinkNLP delivers 600k tokens/second speed on browsers (MBP M1)
What are some alternatives?
afinn - AFINN sentiment analysis in Python
nlp.js - An NLP library for building bots, with entity extraction, sentiment analysis, automatic language identify, and so more
nlphose - Enables creation of complex NLP pipelines in seconds, for processing static files or streaming text, using a set of simple command line tools. Perform multiple operation on text like NER, Sentiment Analysis, Chunking, Language Identification, Q&A, 0-shot Classification and more by executing a single command in the terminal. Can be used as a low code or no code Natural Language Processing solution. Also works with Kubernetes and PySpark !
ml-classify-text-js - Machine learning based text classification in JavaScript using n-grams and cosine similarity
malaya - Natural Language Toolkit for Malaysian language, https://malaya.readthedocs.io/
Recognizers-Text - Microsoft.Recognizers.Text provides recognition and resolution of numbers, units, date/time, etc. in multiple languages (ZH, EN, FR, ES, PT, DE, IT, TR, HI, NL. Partial support for JA, KO, AR, SV). Packages available at: https://www.nuget.org/profiles/Recognizers.Text, https://www.npmjs.com/~recognizers.text
BERTweet - BERTweet: A pre-trained language model for English Tweets (EMNLP-2020)
DataTurks - ML data annotations made super easy for teams. Just upload data, add your team and build training/evaluation dataset in hours.
trankit - Trankit is a Light-Weight Transformer-based Python Toolkit for Multilingual Natural Language Processing
wink-mqtt-rs - MQTT Relay for the Jailbroken Wink Hub v1, with Home Assistant MQTT autodiscovery support
nlp_compromise - modest natural-language processing
echarts4r - 🐳 ECharts 5 for R