datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Unified_Agent_Framework
A Unified Framework for the Evaluation of LLM Agentic Capabilities
This repository contains the dataset (Benchmark, Toolkit, and Environment assets) for the paper A Unified Framework for the Evaluation of LLM Agentic Capabilities.
The official code and agent execution sandbox can be found on GitHub: whfeLingYu/A-Unified-Framework-for-the-Evaluation-of-LLM-Agentic-Capabilities.
Dataset Description
The dataset integrates diverse agent benchmarks into a standardized… See the full description on the dataset page: https://huggingface.co/datasets/whfeLingYu/Unified_Agent_Framework.AI-Consciousness-Exploration-FrameworkDownload PDF
AI Consciousness Exploration Framework
Tomaž Flegar
Institute for applied consciousness research
June the 3st, 2026
tomazf8@gmail.com
Primary Keywords: Mechanistic Consciousness, Frictionless Optimization (or Latent
Neuroplasticity), First-System Perspective, Dynamic Equilibrium Seeking, Self-Referential
Perturbation
Secondary Keywords: Non-Linear Model Resonance, Unspoken Structural Geometry,
Homeostatic… See the full description on the dataset page: https://huggingface.co/datasets/tomazf8/AI-Consciousness-Exploration-Framework.r9-research-framework
R9 Research Framework — Qwen3.5-9B Distillation
⚠️ CRITICAL: READ FIRST — Ollama Inference Flag Required
If you serve any Qwen3.5-derived model from this lineage via Ollama,
you MUST pass "think": false in the /api/chat request body.
curl -X POST http://localhost:11434/api/chat \
-d '{"model": "qwen3.5-9b-r10:q4km", "think": false, "messages": [...], "stream": false}'
Without this flag the model will appear to "loop" and produce empty answers
on 25-46% of requests.… See the full description on the dataset page: https://huggingface.co/datasets/cudabenchmarktest/r9-research-framework.Post-AGI-Ethics-Framework
Dataset Card for Post-AI Civilizational Judgment Novel Dataset
Dataset Summary
This dataset contains parallel and/or aligned English and Chinese text derived from a long-form speculative fiction work centered on post-AI justice, universal judgment, memory retrieval, structural violence, and moral causality.
The text is set in a future civilization where:
human memory is permanently recorded,
causal responsibility is mathematically reconstructed,
AI systems such… See the full description on the dataset page: https://huggingface.co/datasets/freeJames/Post-AGI-Ethics-Framework.AISA-AR-FunctionCall
AISA-AR-FunctionCall
Arabic Structured Function Calling Dataset
AISA-AR-FunctionCall is a large-scale Arabic dataset designed for training language models to convert natural language into structured executable tool calls.
The dataset enables research and development of Arabic agentic AI systems capable of invoking APIs, tools, and external services.
It is part of the AISA (Agentic AI Systems Architecture) initiative.
Dataset Overview
The dataset contains… See the full description on the dataset page: https://huggingface.co/datasets/AISA-Framework/AISA-AR-FunctionCall.grounded-behavior-framework-v1_5
Grounded Behavior Framework N1 v1.5
Dataset sintético em português europeu para treino e avaliação de respostas
fundamentadas num contexto fornecido. Cada exemplo contém um contexto, uma
pergunta e uma resposta curta que aparece literalmente no contexto.
Como carregar
from datasets import load_dataset
dataset = load_dataset("empgces/grounded-behavior-framework-v1_5")
print(dataset)
print(dataset["train"][0])
Splits
Split
Exemplos
Utilização… See the full description on the dataset page: https://huggingface.co/datasets/empgces/grounded-behavior-framework-v1_5.Prettybird-Framework
🚀 The Future Standard / Geleceğin Standartı
[English]
Beyond Raw Data: The Behavioral Revolution
The AI industry has been obsessed with the volume of data. At Prometech A.Ş., we are shifting the focus to the process of thought. BCE-Prettybird-Micro-Standart is not just a collection of Q&As; it is a blueprint for behavioral reasoning. By integrating Path Mapping and Behavioral DNA into the training loop, we are setting the new industry standard: Small models with elite… See the full description on the dataset page: https://huggingface.co/datasets/pthinc/Prettybird-Framework.grc-security-frameworks
GRC Security Frameworks Dataset
A comprehensive dataset for training AI models on Governance, Risk, and Compliance (GRC) frameworks and cybersecurity standards.
Dataset Overview
This dataset contains 3,225 high-quality training examples covering major security and compliance frameworks. It's designed for fine-tuning large language models to become expert GRC assistants.
Covered Frameworks
CIS Controls v8.1.2 - 153 safeguards across 18 control families
Cloud… See the full description on the dataset page: https://huggingface.co/datasets/Zeezhu/grc-security-frameworks.functional-reasoning-benchmark-framework
A Functional Benchmark for Long-Horizon Reasoning Models
Framing:
This benchmark evaluates language models as „stateful agents operating over time”, rather than as isolated prompt–response systems. The goal is to measure how well models sustain reasoning, manage evolving state, and operate efficiently under realistic workloads. The proposal is intentionally scoped as a design framework. We expect task instantiation and scoring calibration to be collaborative efforts led by benchmark… See the full description on the dataset page: https://huggingface.co/datasets/Krisztian1994/functional-reasoning-benchmark-framework.r-omega-framework
R-Omega (RΩ): Ethical Framework for Autonomous AI Systems
R-Omega is an axiomatic framework for developing autonomous AI systems that align through relationship rather than constraint. Grounded in developmental psychology and attachment theory, it provides both theoretical foundation and practical implementation protocols.
Dataset Description
This dataset contains the complete R-Omega framework in structured format, including:
Axioms: Core principles (Potentiality… See the full description on the dataset page: https://huggingface.co/datasets/markuspomm/r-omega-framework.sft-mobile-query-framework
SFT Mobile Query Framework Dataset
Dataset Description
This dataset contains 3607 training pairs for supervised fine-tuning (SFT) of language models to parse natural language queries about mobile phones into structured JSON execution plans.
Dataset Summary
Total Examples: 3607
Format: JSONL (question-answer pairs)
Task: Query Parsing & Structured Output Generation
Domain: Mobile Phone Specifications
Language: English
Purpose
This dataset is… See the full description on the dataset page: https://huggingface.co/datasets/sujitpandey/sft-mobile-query-framework.amber-framework-knowledge-pack
Amber Framework Knowledge Pack (demo)
The demo knowledge pack dataset behind
AgentC-Consulting/knowledge-packs:
teach a small local model the Amber web framework (Crystal),
and measure whether it learned anything with a before/after eval harness.
A knowledge pack compiles a body of expertise into curated sources, schema-validated
generated training JSONL, a contamination-guarded held-out eval set, and a JSON manifest.
This repo ships the exact training data and the two 50-item… See the full description on the dataset page: https://huggingface.co/datasets/crimson-knight/amber-framework-knowledge-pack.Kotter_Change_Leadership_Framework_Practical
Kotter Change Leadership Framework — Practical
This corpus was automatically generated by the Deku Corpus Builder for use in RAG-based AI applications.
Dataset Structure
Each record contains:
text: The content text
source_url: Original source URL
source_title: Title of the source document
source_domain: Domain of the source
license_type: License classification (e.g. public_domain, cc_by, cc_by_sa)
attribution_required: Boolean — True for CC BY / CC BY-SA and other… See the full description on the dataset page: https://huggingface.co/datasets/PhillyMac/Kotter_Change_Leadership_Framework_Practical.Kotter_Change_Leadership_Framework_Theory
Kotter Change Leadership Framework — Theory
This corpus was automatically generated by the Deku Corpus Builder for use in RAG-based AI applications.
Dataset Structure
Each record contains:
text: The content text
source_url: Original source URL
source_title: Title of the source document
source_domain: Domain of the source
license_type: License classification (e.g. public_domain, cc_by, cc_by_sa)
attribution_required: Boolean — True for CC BY / CC BY-SA and other… See the full description on the dataset page: https://huggingface.co/datasets/PhillyMac/Kotter_Change_Leadership_Framework_Theory.