Omkar2118/datasets huggingface dataset:
COVID-19-TweetIDs
Full name: Tracking Social Media Discourse About the COVID-19 Pandemic: Development of a Public Coronavirus Twitter Data Set

Since the inception of our collection, we have actively maintained and updated our GitHub repository on a weekly basis. We have published over 123 million tweets, with over 60% of the tweets in English. This paper also presents basic statistics that show that Twitter activity responds and reacts to COVID-19-related events.
Vulnerability Java Dataset

The dataset consists of two versions: $X_1$ with $P_3$ and $X_1$ without $P_3$, where $P_3$ represents a set of random unchanged functions from vulnerability fixing commits. This dataset is designed for finetuning large language models to detect vulnerabilities in code. It can be used for training and evaluating models in automated vulnerability detection tasks.

Source: [Finetuning Large Language Models for Vulnerability Detection](https://github.com/rmusab/vul-llm-finetune/tree/main/Datasets)

Introducing paper: Finetuning Large Language Models for Vulnerability Detection
RealVul
Full name: RealVul-Vulnerability Dataset following realistic settings

This is a C++ vulnerability detection dataset following realistic settings. For details, please check our study Revisiting the Performance of Deep Learning-Based Vulnerability Detection on Realistic Datasets (Partha et al., 2024)

The column names are self-describing. The most important two columns are,

Target: int: vulnerable to not.
Code: str: the code segment.
For details, please check our huggingface repository.

Introducing paper: Revisiting the Performance of Deep Learning-Based Vulnerability Detection on Realistic Datasets
SafeAligner

This dataset provides harmful queries and their corresponding safe and harmful responses.

Introducing paper: SafeAligner: Safety Alignment against Jailbreak Attacks via Response Disparity Guidance