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doc: upadte README.md
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18 changes: 16 additions & 2 deletions README.Rmd
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<div style="text-align: justify">


**flaiR** is an R package that provides convenient access to [flairNLP/flair](https://github.com/flairNLP/flair), a powerful Python-based NLP toolkit developed by Humboldt University of Berlin. The R package is maintained by [Yen-Chieh Liao](https://davidycliao.github.io) ([University of Birmingham](https://www.birmingham.ac.uk/research/centres-institutes/centre-for-artificial-intelligence-in-government)) and [Stefan Müller](https://muellerstefan.net) from [Next Generation Energy Systems](https://www.nexsys-energy.ie) and [Text and Policy Research Group](https://text-and-policy.com) at UCD.
**flaiR** is an R package that provides convenient access to [flairNLP/flair](https://github.com/flairNLP/flair), a powerful Python-based NLP toolkit developed by Humboldt University of Berlin. **flaiR** package is maintained by [Yen-Chieh Liao](https://davidycliao.github.io) ([University of Birmingham](https://www.birmingham.ac.uk/research/centres-institutes/centre-for-artificial-intelligence-in-government)) and [Stefan Müller](https://muellerstefan.net) from [Next Generation Energy Systems](https://www.nexsys-energy.ie) and [Text and Policy Research Group](https://text-and-policy.com) at UCD.

Through **flaiR**, R users can easily utilize and combine various word embeddings, train deep learning models, and fine-tune the latest transformer models from Hugging Face, bridging advanced NLP functionality with popular quantitative text analysis toolkits like quanteda in the R environment.
Through **flaiR**, R users can easily utilize and combine various word embeddings, train deep learning models, and fine-tune the latest transformer models from Hugging Face, bridging advanced NLP techniques with popular quantitative text analysis toolkits like quanteda in the R environment.


<!-- Our team trains and fine-tunes the models with Flair in [our projects](). -->
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<br>



## Some Useful Cases

- [Working Various Embedding Framework in R](https://davidycliao.github.io/flaiR/articles/tutorial.html#embedding)

- [Beyond the 'à la carte' Embeddings Regression](https://davidycliao.github.io/flaiR/articles/tutorial.html#embedding)

- [Finetune Transformers in R](https://davidycliao.github.io/flaiR/articles/tutorial.html#finetune-transformers)

For more detailed tutorial instructions, please visit [Flair NLP and flaiR for Social Science](https://davidycliao.github.io/flaiR/articles/quickstart.html#flair-installation).

<br>


## Installation via <u>__`GitHub`__</u>


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27 changes: 22 additions & 5 deletions README.md
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**flaiR** is an R package that provides convenient access to
[flairNLP/flair](https://github.com/flairNLP/flair), a powerful
Python-based NLP toolkit developed by Humboldt University of Berlin. The
R package is maintained by [Yen-Chieh
Python-based NLP toolkit developed by Humboldt University of Berlin.
**flaiR** package is maintained by [Yen-Chieh
Liao](https://davidycliao.github.io) ([University of
Birmingham](https://www.birmingham.ac.uk/research/centres-institutes/centre-for-artificial-intelligence-in-government))
and [Stefan Müller](https://muellerstefan.net) from [Next Generation
Expand All @@ -36,16 +36,33 @@ Research Group](https://text-and-policy.com) at UCD.

Through **flaiR**, R users can easily utilize and combine various word
embeddings, train deep learning models, and fine-tune the latest
transformer models from Hugging Face, bridging advanced NLP
functionality with popular quantitative text analysis toolkits like
quanteda in the R environment.
transformer models from Hugging Face, bridging advanced NLP techniques
with popular quantitative text analysis toolkits like quanteda in the R
environment.

<!-- Our team trains and fine-tunes the models with Flair in [our projects](). -->

</div>

<br>

## Some Useful Cases

- [Working Various Embedding Framework in
R](https://davidycliao.github.io/flaiR/articles/tutorial.html#embedding)

- [Beyond the ‘à la carte’ Embeddings
Regression](https://davidycliao.github.io/flaiR/articles/tutorial.html#embedding)

- [Finetune Transformers in
R](https://davidycliao.github.io/flaiR/articles/tutorial.html#finetune-transformers)

For more detailed tutorial instructions, please visit [Flair NLP and
flaiR for Social
Science](https://davidycliao.github.io/flaiR/articles/quickstart.html#flair-installation).

<br>

## Installation via <u>**`GitHub`**</u>

<div style="text-align: justify">
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