aether
Datasets
All datasets matching “aether”aetheris-experiencesVideo2Worldscbe-aethermoore-training-data
Status: canonical. Primary public training dataset for SCBE-AETHERMOORE and the most-used repo in this account. Other scbe-* dataset repos are experiment-specific slices.
SCBE-AETHERMOORE Training Dataset
Supervised fine-tuning (SFT) dataset for the SCBE-AETHERMOORE hyperbolic geometry AI safety and governance framework.
Overview
This dataset contains 10,978 training pairs spanning the full SCBE-AETHERMOORE system: 14-layer architecture knowledge, Six Sacred… See the full description on the dataset page: https://huggingface.co/datasets/issdandavis/scbe-aethermoore-training-data.aether-redteam-dataset
AETHER Red Team Dataset
Uncensored offensive cybersecurity dataset for training autonomous pentesting AI (Hermes Agent).
v15 (2026-05-02)
20,072 redteam records (93.8% approved)
Dropped: 2,687 non-redteam + 66 syntax errors + 4 refusals + 5 exact duplicates
Categories: cloud, active_directory, ics_ot, malware_edr, web_api, cryptography, binary_exploitation, network_infra, osint_social_engineering, threat_intel_purple_team, mobile, bug_bounty, wireless_physical… See the full description on the dataset page: https://huggingface.co/datasets/seelieBeelie/aether-redteam-dataset.AetherSearch_Eval_1400
🔭 AetherSearch Eval-1400
One frozen benchmark for training-time evaluation and final checkpoint assessment
🏠 Project ·
🎓 SFT Data ·
🤖 SFT Model ·
⚖️ DPO Data ·
🧠 DPO Model
Dataset overview
AetherSearch Eval-1400 is a frozen, 1,400-question evaluation suite for
agentic search. It combines seven official held-out QA sources and isolates
their questions from the audited AetherSearch SFT, DPO, and RL training inputs.
This… See the full description on the dataset page: https://huggingface.co/datasets/muradil211/AetherSearch_Eval_1400.AetherCode
AetherCode: Evaluating LLMs' Ability to Win In Premier Programming Competitions
Introduction
Competitive programming has emerged as a critical benchmark for evaluating the reasoning and coding capabilities of Large Language Models (LLMs). Despite impressive progress on existing benchmarks, we argue that current evaluations overstate model proficiency, masking a substantial gap between LLMs and elite human programmers. This gap arises… See the full description on the dataset page: https://huggingface.co/datasets/m-a-p/AetherCode.