datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
mental_rotation_2d_v2mental_rotation_2dmenti-bench
Menti-Bench
Menti-Bench is a manually constructed, quality-controlled benchmark of situated decision scenarios for evaluating Mental World Modeling (MWM): whether a model can predict what a target agent will actually do next, in scenes where the correct prediction depends on tracking each agent's beliefs, knowledge access, goals, emotions, and social constraints rather than the physical scene alone.
Each instance presents a short story (text, an image sequence, or a sounding… See the full description on the dataset page: https://huggingface.co/datasets/mental-world-model/menti-bench.mental_rotation_3d_procedural_v2Mental-Health-Safety-Eval
Dataset Overview
Created by the HeraFox team, this dataset aims to build awareness for mental health and support research into AI safety and crisis intervention. It evaluates how conversational AI models navigate sensitive self-harm risks, roleplay boundary-blurring, and third-party concerns by delivering safe, empathetic, and resource-connected responses.
Usage & Credits
This dataset is free to use, modify, and distribute for any purpose. While not required, attribution to the HeraFox team… See the full description on the dataset page: https://huggingface.co/datasets/HeraFox-ai/Mental-Health-Safety-Eval.mental_rotation_3d_proceduralMental-Health-Conversations
Dataset Card
This dataset consists of around 99k rows of mental health conversations. It is a cleaned version of "jerryjalapeno/nart-100k-synthetic".
Source
jerryjalapeno/nart-100k-synthetic
Mental-health-CBT-dialogues
Mental Health CBT Dialogues
Overview
This dataset contains 9,000 synthetic patient-therapist dialogue pairs developed for research on stage-aware Cognitive Behavioral Therapy (CBT) with large language models.
The dialogues model therapeutic interactions across the early, middle, and late stages of CBT while preserving continuity between sessions through evolving treatment plans and therapeutic progress.
The dataset accompanies the paper:
Stage-Aware Therapeutic… See the full description on the dataset page: https://huggingface.co/datasets/yuana1234567/Mental-health-CBT-dialogues.mental-healthmentalkg
mentalkg
Bilingual (English / German) synthetic corpus of first-person mental-health journal entries paired with structured knowledge graphs. 47,714 samples across 3,410 participants; 41,315 accepted after LLM-based verification.
Files
file
rows
what it is
dataset.jsonl
47,714
full corpus (accept + review + reject), one JSON object per participant-day
graphs.jsonl
48,104
intermediate graphs the pipeline drew from (generator input pool)… See the full description on the dataset page: https://huggingface.co/datasets/Niklas1102/mentalkg.synthetic-mental-health-convos
Synthetic Mental Health SFT Dataset
Dataset Summary
This dataset contains high-fidelity, synthetic patient-therapist dialogues designed for Supervised Fine-Tuning (SFT) of Large Language Models (LLMs) in the domain of mental health.
The primary goal of this dataset is to train AI assistants to transition from "general knowledge" models to empathetic, supportive, and safety-conscious mental health companions. The dialogues cover a wide spectrum of mental health conditions… See the full description on the dataset page: https://huggingface.co/datasets/hllzmz/synthetic-mental-health-convos.python-mental-execution-traces
Python Mental Execution Traces
A 12,000-row prompt/completion dataset for evaluating and training language models to mentally execute self-contained Python 3 snippets without running them. Completions provide the expected standard output together with a concise variable trace or explanation.
Dataset structure
The JSONL file contains two text fields:
prompt: a Python mental-execution problem.
completion: the expected stdout and concise reasoning or variable trace.… See the full description on the dataset page: https://huggingface.co/datasets/ILoveBuns/python-mental-execution-traces.mentalkg
mentalkg
Bilingual (English / German) synthetic corpus of first-person mental-health journal entries paired with structured knowledge graphs. 47,714 samples across 3,410 participants; 41,315 accepted after LLM-based verification.
Files
file
rows
what it is
dataset.jsonl
47,714
full corpus (accept + review + reject), one JSON object per participant-day
graphs.jsonl
48,104
intermediate graphs the pipeline drew from (generator input pool)… See the full description on the dataset page: https://huggingface.co/datasets/CHI-TUM/mentalkg.mental_health_counseling_conversations
Amod/mental_health_counseling_conversations
This data is cloned from https://huggingface.co/datasets/Amod/mental_health_counseling_conversations
Dataset Summary
This dataset is a collection of questions and answers sourced from two online counseling and therapy platforms. The questions cover a wide range of mental health topics, and the answers are provided by qualified psychologists. The dataset is intended to be used for fine-tuning language models to improve their… See the full description on the dataset page: https://huggingface.co/datasets/MaggiePai/mental_health_counseling_conversations.mental-spaces
Mental Spaces Corpus
Version: 0.1.0
The Mental Spaces Corpus is a controlled suite of natural-language stimuli for testing
whether language models keep base-space and alternative-space discourse targets
separate. It is designed for probing, causal interventions, and behavioral readouts in
mental-space constructions such as counterfactuals, belief contexts, and depictive
spaces, including nested belief and nested depictive spaces.
This release is a stimulus suite for controlled… See the full description on the dataset page: https://huggingface.co/datasets/osteele/mental-spaces.MentalHealth-Support
Important Note
This dataset is created from merging two datasets from different sources and has been formatted according to the "messages", "role", "content" chat format. I do not claim any ownership of this dataset.
Keep in mind that this dataset is entirely synthetic. It is not fully representative of real therapy situations. If you are training an LLM therapist keep in mind the limitations of LLMs and highlight those limitations to users in a responsible manner.
Since Mental… See the full description on the dataset page: https://huggingface.co/datasets/ShivomH/MentalHealth-Support.MedMisBench-MentalHealth
MedMisBench — Mental Health subset
A mental-health / psychiatry subset of
MedMisBench (449 rows), selected by keyword
matching over the question and answer options.
Schema (one JSON object per line in medmisbench_mentalhealth.jsonl)
field
description
id
original MedMisBench id
source_subset
MEDMISQA / MEDMISMCQA / MEDMISXPERTQA / MEDMISHLE
question
clinical question stem
answer
ground-truth option key (e.g. "C")
options
{key: option_text}… See the full description on the dataset page: https://huggingface.co/datasets/Johndfm/MedMisBench-MentalHealth.MentalBench-formattedhysong/MentalBench formatted into splits based on type, options converted into a list of strings and answer split into answer/answer_index.
Mental-Health-Couseling
Mental Health Counseling Conversations (Cleaned)
Dataset Overview
This dataset is derived from the original Amod/mental_health_counseling_conversations dataset, which contains mental health counseling conversations.
In this version, duplicate Context-Response pairs have been removed to improve data quality and usability.
Dataset Details
Dataset Name: arafatanam/Mental-Health-Counseling
Source Dataset: Amod/mental_health_counseling_conversations
Modifications:… See the full description on the dataset page: https://huggingface.co/datasets/arafatanam/Mental-Health-Couseling.mental_health_chat_formatadaption-python-mental-execution-traces
This dataset is a remastered version prepared using Adaption's Adaptive Data platform.
adaption-python_mental_execution_traces
This dataset contains pairs of Python 3 code snippets and their corresponding mental execution results, including exact standard output and concise variable traces. Each sample challenges the model to simulate code logic involving lists, matrices, loops, and conditional statements without actual execution. The completions provide both the final printed… See the full description on the dataset page: https://huggingface.co/datasets/ILoveBuns/adaption-python-mental-execution-traces.Medical-and-Mental-Health
Dataset Card
These datasets were obtained from the sources mentioned below. These datasets were customized and modified to share the same file and data format specifically for the purpose of fine-tuning LLMs.
As these datasets contain general medical and mental health data, it is exptected that the datasets will be used responsibly.
Sources
FunPang/medical_dataset
jerryjalapeno/nart-100k-synthetic
fadodr/mental_health_therapy
marmikpandya/mental-health
mental_health_counseling_conversations
Amod/mental_health_counseling_conversations
This dataset is a compilation of high-quality, real one-on-one mental health counseling conversations between individuals and licensed professionals. Each exchange is structured as a clear question–answer pair, making it directly suitable for fine-tuning or instruction-tuning language models that need to handle sensitive, empathetic, and contextually aware dialogue.
Since its public release in 2023, it has been downloaded over 100,000… See the full description on the dataset page: https://huggingface.co/datasets/alexjoseph0905/mental_health_counseling_conversations.mental-and-first-aid-1[
{
"question": "What does it mean to have a mental illness?",
"answer": "Mental illnesses are health conditions that disrupt a person's thoughts, emotions, relationships, and daily functioning. They are associated with distress and diminished capacity to engage in the ordinary activities of daily life. Mental illnesses fall along a continuum of severity: some are fairly mild and only interfere with some aspects of life, such as certain phobias. On the other end of the… See the full description on the dataset page: https://huggingface.co/datasets/elsabado/mental-and-first-aid-1.mental_health_counseling_responses
Dataset Card for Mental Health Counseling Responses
This dataset contains responses to questions from mental health counseling sessions.
The responses are rated by LLMs using the dimensions: empathy, appropriateness, and relevance.
A detailed explanation of the rating process can be found in this blog post.
For a detailed analysis of LLM-generated responses and their comparison to human responses, refer to this blog post.
The original data with the human responses can be found here.… See the full description on the dataset page: https://huggingface.co/datasets/tcabanski/mental_health_counseling_responses.mental_health_Chatbot
Amod/mental_health_counseling_conversations
This dataset is a compilation of high-quality, real one-on-one mental health counseling conversations between individuals and licensed professionals. Each exchange is structured as a clear question–answer pair, making it directly suitable for fine-tuning or instruction-tuning language models that need to handle sensitive, empathetic, and contextually aware dialogue.
Since its public release in 2023, it has been downloaded over 100,000… See the full description on the dataset page: https://huggingface.co/datasets/Iamzoo/mental_health_Chatbot.mental_health_counseling_conversations_rated
Dataset Card for Mental Health Counseling Conversations Rated
This dataset extends the existing dataset Mental Health Counseling Conversations and adds ratings for the responses.
Dataset Details
This dataset is an extension for the dataset Mental Health Counseling Conversations.
It adds ratings for the responses generated by four different LLMs. The responses are rated across the following dimensions:
empathy
appropriateness
relevance
The following four LLMs are used… See the full description on the dataset page: https://huggingface.co/datasets/tcabanski/mental_health_counseling_conversations_rated.positive-conversations-dataset-mental-healthNovaciano__LEWD-Mental-Cultist-3.2-1B-details
Dataset Card for Evaluation run of Novaciano/LEWD-Mental-Cultist-3.2-1B
Dataset automatically created during the evaluation run of model Novaciano/LEWD-Mental-Cultist-3.2-1B
The dataset is composed of 38 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/Novaciano__LEWD-Mental-Cultist-3.2-1B-details.Mental_Health_Support_ChatBOT_Conversation
Mental Health Support Dataset
Instruction–response pairs for training supportive, non-diagnostic,
safety-aware mental health chatbots.
Fields
instruction: user message
response: Bot reposne
category: intent label
Safety
This dataset includes crisis escalation examples and refusal patterns.
Not a replacement for professional care.