wink-nlp
dasher-web
| wink-nlp | dasher-web | |
|---|---|---|
| 21 | 1 | |
| 1,143 | 42 | |
| 1.0% | - | |
| 8.1 | 5.8 | |
| 12 days ago | about 2 months ago | |
| JavaScript | JavaScript | |
| MIT License | MIT License |
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wink-nlp
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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
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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)
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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)
dasher-web
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Show HN: Next-token prediction in JavaScript – build fast LLMs from scratch
Their library was actually made for dasher.. http://www.inference.org.uk/dasher/ - there was a web version being made (https://github.com/dasher-project/dasher-web We hit a bottleneck with the graphics driving. Note in dasher pretty much the entire tree is in dynamic view). Now this may help to understand the use case. Dasher is for people with disabilities who cant speak. It needs to be a personalised LM that trains on the fly and and keeps track of new words/sentences. But in truth too, utterances are usually small.
Don't get too knocked back by comments. A) If it works - it works. B) Your learning is as valuable as the outcome.
Oh have a look at https://imagineville.org/software/ for some other things that may be of interest..
What are some alternatives?
nlp.js - An NLP library for building bots, with entity extraction, sentiment analysis, automatic language identify, and so more
ml-classify-text-js - Machine learning based text classification in JavaScript using n-grams and cosine similarity
wink-eng-lite-model - English lite language model for wink-nlp.
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
DataTurks - ML data annotations made super easy for teams. Just upload data, add your team and build training/evaluation dataset in hours.
wink-mqtt-rs - MQTT Relay for the Jailbroken Wink Hub v1, with Home Assistant MQTT autodiscovery support
echarts4r - 🐳 ECharts 5 for R
WantWords - An open-source online reverse dictionary.
nodejs-language - Node.js client for Google Cloud Natural Language: Derive insights from unstructured text using Google machine learning.
chatternet-client-http
malaya - Natural Language Toolkit for Malaysian language, https://malaya.readthedocs.io/
st-chat - Streamlit Component, for a Chatbot UI