Hugging Face Dataset - bfuzzy1/gunny_x
Every veteran knows and has had a 'Gunny': Semper Fidelis. This dataset is designed for conversational AI systems to assist veterans from various military branches, including U.S. and U.K. armed forces.
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Every veteran knows and has had a 'Gunny': Semper Fidelis. This dataset is designed for conversational AI systems to assist veterans from various military branches, including U.S. and U.K. armed forces. The dataset uses multiple personas from different branches (9) to be exact, each dedicated to providing support for veterans dealing with PTSD and transitioning to civilian life. The personas offer advice rooted in discipline, accountability, and mental resilience, while maintaining the appropriate tone and ethos of each military branch. Each persona emphasizes the importance of seeking professional help when necessary, without substituting for therapy, but there is no guarentee. All data was generated using Meta's - Llama-3.2-3B-Instruct.
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IC-AnnoMI: In-Context MI Dialogues - GitHub Repository
The IC-AnnoMI repository contains source code and a synthetic dataset generated through in-context zero-shot LLM prompting for mental health and therapeutic counselling. IC-AnnoMI is a project that generates contextual MI dialogues using large language models (LLMs). The project contains source code and a synthetic dataset generated through zero-shot prompts, aiming to address the data scarcity and inherent bias problems in mental health and therapeutic consultation.
electronic media datasets - Mental Health Datasets
An evolving list of electronic media datasets used to model mental health status. This repository curates a variety of datasets from different sources, including social media platforms, online forums, and academic studies, to support research in mental health modeling and AI applications.
Hugging Face Dataset - lsy641/PsyQA
The data is originally source from (Sun et al,2021). (Liu et al, 2023) processed the data to make it a dataset vis huggingface api with taining/validation/testing splitting