wink-eng-lite-model
afinn
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| wink-eng-lite-model | afinn | |
|---|---|---|
| 5 | 1 | |
| 10 | 439 | |
| - | - | |
| 0.0 | 2.6 | |
| almost 3 years ago | about 2 years ago | |
| Jupyter Notebook | ||
| MIT License | Apache License 2.0 |
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wink-eng-lite-model
- SuperCharge Input Field for a Dictionary Website
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How to run NLP on a PDF file?
winkNLP’s English language lite model uses a pre-trained state machine to recognize named entities.
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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:
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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%.
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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.
afinn
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Is it possible to deploy a large NLP model for free?
I tried lighter deep learning models like DistilBERT, but they performed worse/on-par with a simple dictionary-based model like AFINN . (The use case is scoring the positivity of news headlines). Haven't looked at Spacy though.
What are some alternatives?
wink-nlp - Developer friendly Natural Language Processing ✨
pytorch-sentiment-analysis - Tutorials on getting started with PyTorch and TorchText for sentiment analysis.
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 !
awesome-sentiment-analysis - Repository with all what is necessary for sentiment analysis and related areas
malaya - Natural Language Toolkit for Malaysian language, https://malaya.readthedocs.io/
BERTweet - BERTweet: A pre-trained language model for English Tweets (EMNLP-2020)
SuiSense - Using Artificial Intelligence to distinguish between suicidal and depressive messages (4th Place Congressional App Challenge)
trankit - Trankit is a Light-Weight Transformer-based Python Toolkit for Multilingual Natural Language Processing
n4m-sentiment - Sentiment Analysis for your MaxMSP patches - made easy.
nlp_compromise - modest natural-language processing
API-Danmark - 🇩🇰 Liste over danske API'er