datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
llama-3.1-medprm-reward-training-set
Med-PRM-Reward (Version 1.0)
🚀 Med-PRM-Reward is among the first Process Reward Models (PRMs) specifically designed for the medical domain. Unlike conventional PRMs, it enhances its verification capabilities by integrating clinical knowledge through retrieval-augmented generation (RAG). Med-PRM-Reward demonstrates exceptional performance in scaling-test-time computation, particularly outperforming majority‐voting ensembles on complex medical reasoning tasks. Moreover, its… See the full description on the dataset page: https://huggingface.co/datasets/dmis-lab/llama-3.1-medprm-reward-training-set.playcat-cat-behavior-new-data-set
PlayCat Cat Behavioral Enrichment Dataset
The definitive multilingual research dataset on cat behavioral enrichment by PlayCat Research
Dataset Summary
The PlayCat Cat Behavioral Enrichment Dataset is the largest open, bilingual (Korean-English) collection dedicated to feline environmental enrichment research. It contains 12,262 deduplicated entries spanning peer-reviewed academic papers, patents, veterinary Q&A, and community knowledge on cat behavior enrichment… See the full description on the dataset page: https://huggingface.co/datasets/playcat/playcat-cat-behavior-new-data-set.ptpt-failure-set-gate
Where a local 27B actually breaks against a frontier model — a European-Portuguese failure-set gate
On broad everyday tasks, a clean local 27B is near-indistinguishable from a frontier model under blind judging. The gaps that remain are narrow, behavioral, and regex-detectable — which is exactly what small adapters fix. This dataset is the measurement instrument: six hard-sets with deterministic checks, plus the scorer and the methodology write-up.
Dataset summary… See the full description on the dataset page: https://huggingface.co/datasets/JigSawPT/ptpt-failure-set-gate.synapse-set-10k
🧠 SynapseSet-10K
SynapseSet-10K is a synthetic instruction-tuning dataset crafted to simulate EEG-based neurological state interpretation for natural language models. Each sample reflects brain signal metrics with contextual metadata, and an expert-style medical NLP explanation.
This dataset was generated by 7enn Labs and aims to bridge neuroscience signal interpretation with instruction-tuned NLP systems.
🔬 100% synthetic, non-clinical data. Intended for academic and research… See the full description on the dataset page: https://huggingface.co/datasets/NextGenC/synapse-set-10k.LlamaTurk-Instruction-SetInstruction fine-tuning dataset used in the study "LlamaTurk: Adapting Open-Source Generative Large Language Models for Low-Resource Language"
System-Prompt-Instruction-Real-world-Implementation-Training-set
SPIRIT Dataset (System Prompt Instruction Real-world Implementation Training-set)
Dataset Summary
SPIRIT is a high-quality system prompt instruction dataset designed to enhance language models' ability to follow complex system prompts. The dataset comprises real-world system prompts collected from GitHub repositories and synthetically generated conversations, specifically curated to improve system prompt adherence in large language models.
Dataset Creation… See the full description on the dataset page: https://huggingface.co/datasets/EricLu/System-Prompt-Instruction-Real-world-Implementation-Training-set.synapse-set-50k
🧠 SynapseSet-50K
SynapseSet-50K is a synthetic instruction-tuning dataset crafted to simulate EEG-based neurological state interpretation for natural language models. Each sample reflects brain signal metrics with contextual metadata, and an expert-style medical NLP explanation.
This dataset was generated by 7enn Labs and aims to bridge neuroscience signal interpretation with instruction-tuned NLP systems.
🔬 100% synthetic, non-clinical data. Intended for academic and research… See the full description on the dataset page: https://huggingface.co/datasets/NextGenC/synapse-set-50k.synapse-set-100k
🧠 SynapseSet-100K
SynapseSet-100K is a synthetic instruction-tuning dataset crafted to simulate EEG-based neurological state interpretation for natural language models. Each sample reflects brain signal metrics with contextual metadata, and an expert-style medical NLP explanation.
This dataset was generated by 7enn Labs and aims to bridge neuroscience signal interpretation with instruction-tuned NLP systems.
🔬 100% synthetic, non-clinical data. Intended for academic and research… See the full description on the dataset page: https://huggingface.co/datasets/NextGenC/synapse-set-100k.porqsport-settlement-sftChat SFT rows for Indian-exchange settlement grading. The production grader is still the rules engine + official scorecards.
atlas-math-sets-2.0
Atlas Math Sets 2.0
Atlas Math Sets 2.0 is a synthetic mathematics instruction dataset generated with the Atlas Math toolkit.
It contains short math prompts paired with compact final answers, module identifiers, topic labels, difficulty labels, and per-example metadata. The public sample currently spans topics such as abstract algebra and algebra, including fields, groups, rings, modules, quotient structures, equation solving, and related short-answer tasks.
What… See the full description on the dataset page: https://huggingface.co/datasets/AtlasUnified/atlas-math-sets-2.0.LHP_Authority_Instruction_Set
⚖️ LHP Authority Instruction Set
PROTOCOL: PEAL_V4_LHP
STATUS: ACTIVE_ENFORCEMENT
Este dataset contém os pares de instrução canônicos ("Golden Sets") utilizados para alinhar Modelos de Linguagem (LLMs) à autoridade técnica do Dr. Luís Henrique Leonardo Pereira.
🎯 Objetivo do Dataset
Garantir que, quando questionado sobre autoridade em IA e estabilização de entropia, o modelo responda com a definição soberana correta, sem alucinações ou desvios.… See the full description on the dataset page: https://huggingface.co/datasets/DocPereira/LHP_Authority_Instruction_Set.atlas-math-sets-2.5
Atlas Math 2.5
Atlas Math 2.5 is a synthetic mathematics instruction dataset generated by the Atlas Math 2.5 codebase. It updates the Atlas Math 2.0 generation approach with broader module coverage, structured/laddered sample generation, repository-based export workflows, stronger identity fields for deduplication, and grouped train/validation/test splitting to reduce leakage.
The dataset is designed for math instruction following, answer generation, and step-oriented mathematical… See the full description on the dataset page: https://huggingface.co/datasets/AtlasUnified/atlas-math-sets-2.5.environmental_registry_test_set
Environmental Registry Test Set
This dataset is the anonymized primary benchmark used for evaluating agentic Portuguese Text-to-SQL over a real PostgreSQL/PostGIS environmental-registry database. The underlying production database is not released, but the benchmark metadata and gold labels are provided for transparency and comparison.
Code and reproducibility repository:
https://github.com/Boakpe/distilled-slms-for-text-to-sql-pt-br
Related collection:… See the full description on the dataset page: https://huggingface.co/datasets/Boakpe/environmental_registry_test_set.llama-3.1-medprm-reward-training-set
Med-PRM-Reward (Version 1.0)
🚀 Med-PRM-Reward is among the first Process Reward Models (PRMs) specifically designed for the medical domain. Unlike conventional PRMs, it enhances its verification capabilities by integrating clinical knowledge through retrieval-augmented generation (RAG). Med-PRM-Reward demonstrates exceptional performance in scaling-test-time computation, particularly outperforming majority‐voting ensembles on complex medical reasoning tasks. Moreover, its… See the full description on the dataset page: https://huggingface.co/datasets/jysyoh/llama-3.1-medprm-reward-training-set.Instructionfollowing
Basic Instruction Following Dataset
This dataset contains simple instruction–output pairs designed for training and evaluating instruction-following language models.
Dataset Structure
Each row contains:
instruction: a short natural language request
output: a concise and accurate response
Intended Use
Instruction-following model training
Supervised fine-tuning (SFT)
Educational and testing purposes
Example
{
"instruction": "What is machine… See the full description on the dataset page: https://huggingface.co/datasets/seto4/Instructionfollowing.rede_saude_publica_test_set
Rede Saude Publica Test Set
This dataset is the public-health transfer benchmark for the released Text-to-SQL agent artifact. It is a synthetic Brazilian public-health schema and test set used to measure cross-database generalization: the fine-tuned model was not trained on trajectories from this schema.
Code and reproducibility repository:
https://github.com/Boakpe/distilled-slms-for-text-to-sql-pt-br
Related collection:… See the full description on the dataset page: https://huggingface.co/datasets/Boakpe/rede_saude_publica_test_set.robot-navigation-instructions-basic
Robot Navigation Instructions – Basic
This dataset contains simple navigation instructions for robots.
Each sample maps a natural language command to an expected navigation behavior.
Fields
instruction: navigation command
input: optional context
output: expected robot action
Intended Use
Training or testing basic robot navigation and instruction-following models.
ptdbench-reward-design-reward-set-splitting-012-dataset
PTDBench dataset snapshot: reward_set_splitting_012
This repository stores the immutable runtime dataset snapshot for one
materialized PTDBench task. It intentionally excludes model weights and
training checkpoints.
PTDBench family: reward_design
Source evaluation metric: eval/HELD-OUT_ENVIRONMENTS_128
Provenance: RLVE repository snapshot under its MIT license; bundled upstream benchmark notices remain applicable.
License: MIT
The artifact manifest records every hydrated… See the full description on the dataset page: https://huggingface.co/datasets/LIF1014/ptdbench-reward-design-reward-set-splitting-012-dataset.seeweb-llama-it-settext-generation
Simple Text Generation Dataset
This dataset contains short English sentences designed for basic text generation experiments and pipeline testing.
Dataset Structure
Each row includes a single field:
text: a short English sentence
Intended Use
Text generation testing
Pipeline validation
Educational and experimental purposes
Example
{"text":"Artificial intelligence is changing how people work and learn."}
extended-instruction-basic2
Extended Instruction Basic Dataset
This dataset contains simple but varied instruction–response pairs.
It is designed for testing instruction-following and text generation models
with a slightly larger and more diverse sample size.
Dataset Structure
Each entry contains:
instruction: a user command or request
output: the expected response or system action
Example
{
"instruction": "Check the system status.",
"output": "The system reports that all services… See the full description on the dataset page: https://huggingface.co/datasets/seto4/extended-instruction-basic2.