wink-eng-lite-model
trankit
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| wink-eng-lite-model | trankit | |
|---|---|---|
| 5 | 1 | |
| 10 | 707 | |
| - | - | |
| 0.0 | 5.7 | |
| almost 3 years ago | 12 days ago | |
| Python | ||
| 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.
trankit
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Trankit v1.0.0 - An open-source Transformer-based Multilingual NLP Toolkit for 56 languages is out.
Trankit is written in Python and can be easily installed via pip. Our code and pretrained models are publicly available at: https://github.com/nlp-uoregon/trankit
What are some alternatives?
afinn - AFINN sentiment analysis in Python
spaCy - 💫 Industrial-strength Natural Language Processing (NLP) in Python
wink-nlp - Developer friendly Natural Language Processing ✨
Stanza - Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages
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 !
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
malaya - Natural Language Toolkit for Malaysian language, https://malaya.readthedocs.io/
argilla - Argilla is a collaboration platform for AI engineers and domain experts that require high-quality outputs, full data ownership, and overall efficiency.
BERTweet - BERTweet: A pre-trained language model for English Tweets (EMNLP-2020)
wiktextract - Wiktionary dump file parser and multilingual data extractor
nlp_compromise - modest natural-language processing
flair - A very simple framework for state-of-the-art Natural Language Processing (NLP)