Update app.py

app.py

@@ -62,34 +62,27 @@ Here is an outline of some of the most exciting recent developments in AI:
 
 - 📚 Datasets:
 
-- Universal Dependencies: A collection of annotated corpora for natural language processing in a range of languages, with a focus on dependency parsing.
+**Datasets:**
+
+1. - **Universal Dependencies:** A collection of annotated corpora for natural language processing in a range of languages, with a focus on dependency parsing.
   - [Universal Dependencies official website.](https://universaldependencies.org/)
-  
-- WMT 2014: The fourth edition of the Workshop on Statistical Machine Translation, featuring shared tasks on translating between English and various other languages.
+2. - **WMT 2014:** The fourth edition of the Workshop on Statistical Machine Translation, featuring shared tasks on translating between English and various other languages.
   - [WMT14 website.](http://www.statmt.org/wmt14/)
-
-- The Pile: An English language corpus of diverse text, sourced from various places on the internet.
+3. - **The Pile:** An English language corpus of diverse text, sourced from various places on the internet.
   - [The Pile official website.](https://pile.eleuther.ai/)
-
-- HumanEval: A dataset of English sentences, annotated with human judgments on a range of linguistic qualities.
+4. - **HumanEval:** A dataset of English sentences, annotated with human judgments on a range of linguistic qualities.
   - [HumanEval: An Evaluation Benchmark for Language Understanding](https://github.com/google-research-datasets/humaneval) by Gabriel Ilharco, Daniel Loureiro, Pedro Rodriguez, and Afonso Mendes.
-
-- FLORES-101: A dataset of parallel sentences in 101 languages, designed for multilingual machine translation.
+5. - **FLORES-101:** A dataset of parallel sentences in 101 languages, designed for multilingual machine translation.
   - [FLORES-101: A Massively Multilingual Parallel Corpus for Language Understanding](https://flores101.opennmt.net/) by Aman Madaan, Shruti Rijhwani, Raghav Gupta, and Mitesh M. Khapra.
-
-- CrowS-Pairs: A dataset of sentence pairs, designed for evaluating the plausibility of generated text.
+6. - **CrowS-Pairs:** A dataset of sentence pairs, designed for evaluating the plausibility of generated text.
   - [CrowS-Pairs: A Challenge Dataset for Plausible Plausibility Judgments](https://github.com/stanford-cogsci/crows-pairs) by Andrea Madotto, Zhaojiang Lin, Chien-Sheng Wu, Pascale Fung, and Caiming Xiong.
-
-- WikiLingua: A dataset of parallel sentences in 75 languages, sourced from Wikipedia.
+7. - **WikiLingua:** A dataset of parallel sentences in 75 languages, sourced from Wikipedia.
   - [WikiLingua: A New Benchmark Dataset for Cross-Lingual Wikification](https://arxiv.org/abs/2105.08031) by Jiarui Yao, Yanqiao Zhu, Ruihan Bao, Guosheng Lin, Lidong Bing, and Bei Shi.
-
-- MTEB: A dataset of English sentences, annotated with their entailment relationships with respect to other sentences.
+8. - **MTEB:** A dataset of English sentences, annotated with their entailment relationships with respect to other sentences.
   - [Multi-Task Evaluation Benchmark for Natural Language Inference](https://github.com/google-research-datasets/mteb) by Michał Lukasik, Marcin Junczys-Dowmunt, and Houda Bouamor.
-
-- xP3: A dataset of English sentences, annotated with their paraphrase relationships with respect to other sentences.
+9. - **xP3:** A dataset of English sentences, annotated with their paraphrase relationships with respect to other sentences.
   - [xP3: A Large-Scale Evaluation Benchmark for Paraphrase Identification in Context](https://github.com/nyu-dl/xp3) by Aniket Didolkar, James Mayfield, Markus Saers, and Jason Baldridge.
-
-- DiaBLa: A dataset of English dialogue, annotated with dialogue acts.
+10. - **DiaBLa:** A dataset of English dialogue, annotated with dialogue acts.
   - [A Large-Scale Corpus for Conversation Disentanglement](https://github.com/HLTCHKUST/DiaBLA) by Samuel Broscheit, António Branco, and André F. T. Martins.