docs(README): channge wink-nlp text formatting

README.md

@@ -10,7 +10,7 @@ NLP Functions for amplifying negations, managing elisions, creating ngrams, stem
 Prepare raw text for Natural Language Processing (NLP) using **`wink-nlp-utils`**. It offers a set of [APIs](http://wink.org.in/wink-nlp-utils/) to work on [strings](http://wink.org.in/wink-nlp-utils/#string) such as names, sentences, paragraphs and [tokens](http://wink.org.in/wink-nlp-utils/#tokens) represented as an array of strings/words. They perform the required pre-processing for many ML tasks such as [semantic search](https://www.npmjs.com/package/wink-bm25-text-search), and [classification](https://www.npmjs.com/package/wink-naive-bayes-text-classifier).
 
 <table><tr><td><h3>👉🏽</h3></td><td>
-    We <b>recommend using <a href="https://github.com/winkjs/wink-nlp?tab=readme-ov-file#readme">winkNLP</a></b> for core natural language processing tasks. It <a href="https://winkjs.org/wink-nlp/document.html">performs</a> tokenization, sentence boundary detection, and named entity recognition at a <a href="https://observablehq.com/@winkjs/how-to-measure-winknlps-speed-on-browsers">blazing fast speeds</a>. It supports all your <a href="https://winkjs.org/wink-nlp/leveraging-out.html">text processing needs</a> starting from sentiment analysis, POS tagging, lemmatization, stemming, stop word removal, negation handling, bigrams to frequency table creation and more. <b><a href="https://github.com/winkjs/wink-nlp?tab=readme-ov-file#readme">WinkNLP</a></b> features user-friendly declarative APIs for <a href="https://winkjs.org/wink-nlp/each.html">iteration</a>, <a href="https://winkjs.org/wink-nlp/filter.html">filtering</a>, and <a href="https://winkjs.org/wink-nlp/visualizing-markup.html">text visualization</a>, and <a href="https://winkjs.org/wink-nlp/wink-nlp-in-browsers.html">runs</a> on web browsers.
+    We <b>recommend using <a href="https://github.com/winkjs/wink-nlp?tab=readme-ov-file#readme">winkNLP</a></b> for core natural language processing tasks. <br/><br/>It <a href="https://winkjs.org/wink-nlp/document.html">performs</a> Tokenization, Sentence Boundary Detection, and Named Entity Recognition at a <a href="https://observablehq.com/@winkjs/how-to-measure-winknlps-speed-on-browsers">blazing fast speeds</a>. It supports all your <a href="https://winkjs.org/wink-nlp/leveraging-out.html">text processing needs</a> starting from Sentiment Analysis, POS Tagging, Lemmatization, Stemming, Stop Word Removal, Negation Handling, Bigrams to Frequency Table Creation and more. <br/><br/><b><a href="https://github.com/winkjs/wink-nlp?tab=readme-ov-file#readme">WinkNLP</a></b> features user-friendly declarative APIs for <a href="https://winkjs.org/wink-nlp/each.html">Iteration</a>, <a href="https://winkjs.org/wink-nlp/filter.html">Filtering</a>, and <a href="https://winkjs.org/wink-nlp/visualizing-markup.html">Text Visualization</a>, and <a href="https://winkjs.org/wink-nlp/wink-nlp-in-browsers.html">runs</a> on web browsers.
 </td></tr></table>
 
 ### Installation