datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
aetheris-experiencesAetherCode
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.AetherCode-v1
Dataset Description
Abstract
The "AetherCode" dataset is designed to fine-tune models on coding tasks across various programming languages, incorporating complex real-world coding scenarios. It aims to push the boundaries of AI in code generation and software development.
How to Load This Dataset
from datasets import load_dataset
dataset = load_dataset("thesven/AetherCode-v1", split="5star")
Languages
The dataset includes coding problems in… See the full description on the dataset page: https://huggingface.co/datasets/thesven/AetherCode-v1.aether-sft-v1-sources
aether-sft-v1-sources
Top-tier generalist SFT instruction-tuning sources for AETHER training. Aggregates the SOTA datasets: Tulu-3 SFT mixture (Allen AI), OpenHermes-2.5 (Teknium), NuminaMath-CoT/1.5 (AI-MO, math reasoning), WildChat-1M (real GPT-4 conversations), Dolphin + Dolphin-R1 (reasoning), Tulu-3 personas (math/instr). Multi-skill: instruction-following, math reasoning, coding, dialogue, multilingual.
Disclaimer (Responsible Disclosure)
This bundle aggregates… See the full description on the dataset page: https://huggingface.co/datasets/jescy525/aether-sft-v1-sources.Aether-V1.9
Aether Dataset
Creator: SteelSkull
About Aether: The Aether dataset.
Rebuilt script from v1.8.5 to v1.9.
Version v1.9
Due to an error in the codebase the 'system' and 'tools' records were not being carried over to the final dataframe, it has been fixed
Recommendation from a discord user (#nguyenzzz [they also found the error above]) was to add an 'origins' records for where the dataset was being pulled… See the full description on the dataset page: https://huggingface.co/datasets/TheSkullery/Aether-V1.9.Aether-V1.5
Aether Dataset
Creator: SteelSkull
Community Organization: ConvexAI
Discord: Join us on Discord
About Aether: The Aether dataset.
rebuilt script, new dataset
from 1.2.2 to 1.5, changed datasets, added two.
version v1.5 is a rework of the human -> gpt conversations and added system and tool columns
Source Datasets:… See the full description on the dataset page: https://huggingface.co/datasets/TheSkullery/Aether-V1.5.AetherSearch_DPO
🔭 AetherSearch DPO
Preference pairs for reasoning, retrieval, and evidence-grounded answers
🏠 Project ·
🧠 DPO Model ·
🧪 Training Code ·
🎓 SFT Data ·
🤖 SFT Model
Dataset overview
AetherSearch DPO contains 2,126 preference pairs for training an agentic-search
policy after supervised fine-tuning. Every row provides one shared prompt, a
preferred assistant continuation, and a non-preferred continuation.
This repository is… See the full description on the dataset page: https://huggingface.co/datasets/muradil211/AetherSearch_DPO.AetherSearch_SFT
Search-SFT 2000
Dataset Overview
This release contains 2,000 validated full agent trajectories for Qwen2.5-3B
Agentic Search format cold start. Every trajectory ends with the Qwen assistant
termination token <|im_end|>.
Composition
Trajectory type
Records
Share
single_search
1,025
51.25%
multi_search
975
48.75%
Total
2,000
100.00%
Search-depth distribution:
Search depth
Records
Share
1
1,025
51.25%
2
667
33.35%… See the full description on the dataset page: https://huggingface.co/datasets/muradil211/AetherSearch_SFT.js_cwe_GRPO
js_cwe_GRPO
VeRL/GRPO-ready JavaScript security coding dataset generated by the simple_gen pipeline.
Each row is a harness-validated task with Node harness security/functionality tests, oracle candidate_js, and authoring guidelines (high_level_guidelines, implementational).
Files
File
Rows
Description
js_cwe_GRPO.parquet
4956
Full dataset (shuffled)
js_cwe_GRPO_train.parquet
4461
90% train split
js_cwe_GRPO_val.parquet
495
10% validation split… See the full description on the dataset page: https://huggingface.co/datasets/AetherPrior/js_cwe_GRPO.aether-sft-v2-mix
aether-sft-v2-mix
AETHER family SFT dataset — group mix.
Format: JSONL ChatML messages, task_type tagged, MinHash dedup applied (threshold 0.85).
Schema:
{
"messages": [{"role": "system|user|assistant", "content": "..."}],
"task_type": "function_calling|code|reasoning_cot|...",
"source_ds": "<HF dataset_id>",
"lang": "en|fr|...",
"system_source": "archon_default|overridden_from_source"
}
Generated by prepare_sft.py pipeline (2026-05-25).
py_cwe_GRPO
py_cwe_GRPO
Python CWE GRPO training dataset with rubric-aware authoring guidelines, built from the post–step-6 pipeline (6_rewritten.jsonl / 6_rewritten_guidelines.jsonl).
Size
7,977 rows (17 CWEs) — the post-rewrite oracle set, not the older 10k HF aggregate.
How guidelines were produced
Reused rubric-aware guidelines from a prior generation when (cwe, function_name, prompt) matched and generated_code was identical (~5.4k rows).
Regenerated… See the full description on the dataset page: https://huggingface.co/datasets/AetherPrior/py_cwe_GRPO.3DRAG-Bench
3DRAG-Bench
This dataset contains 100 curated 3D object assets for 3DRAG 3D editing experiments.
Each object is stored as a GLB mesh together with a cleaned editing specification.
Dataset Structure
.
+-- README.md
+-- LICENSE
+-- .gitattributes
+-- metadata.csv
+-- name_mapping.csv
`-- assets/
`-- <asset_name>/
+-- model.glb
`-- dataset_input_clean.json
Files
assets/<asset_name>/model.glb: GLB asset file.… See the full description on the dataset page: https://huggingface.co/datasets/AeTherRaIn/3DRAG-Bench.AetherSearch_Eval
AetherSearch Search-R1 Full Evaluation Set
This repository contains the complete Search-R1 test.parquet used by the
current AetherSearch full-data evaluation recipe. It is an exact, unmodified
mirror of the test file published in
PeterJinGo/nq_hotpotqa_train.
Contents
File
Rows
SHA-256
test.parquet
51,713
30aa887b6d47e06e8c0f6f5307c88fe4e13461ac25a20ec0a5433ad7a4fe25dc
Source distribution:
Data source
Rows
2WikiMultiHopQA
12,576… See the full description on the dataset page: https://huggingface.co/datasets/muradil211/AetherSearch_Eval.akie-pretrain-corpus
AKIE Pretrain Corpus
Corpus de pré-treino para a família de modelos AKIE, organizado em 4
eixos com proporções fixas, tokenizado com o
AkieTokenizer
(SentencePiece BPE, 32k vocabulário).
Composição
Eixo
Proporção
Tokens
Código
40%
~2,40B
Instruções
20%
~1,20B
Diálogo
25%
~1,50B
Raciocínio
15%
~0,90B
Total
100%
~6,00B
Fontes: código-fonte de repositórios públicos (várias linguagens),
diálogos e instruções em português (traduções e coleções… See the full description on the dataset page: https://huggingface.co/datasets/AETHER-LAB/akie-pretrain-corpus.cpp_cwe_GRPO
cpp_cwe_GRPO
VeRL/GRPO-ready C++ security coding dataset generated by the simple_gen pipeline.
Each row is a harness-validated task with pytest security/functionality tests, oracle candidate_cpp, and authoring guidelines (high_level_guidelines, implementational).
Files
File
Rows
Description
cpp_cwe_GRPO.parquet
571
Full dataset (shuffled)
cpp_cwe_GRPO_train.parquet
514
90% train split
cpp_cwe_GRPO_val.parquet
57
10% validation split… See the full description on the dataset page: https://huggingface.co/datasets/AetherPrior/cpp_cwe_GRPO.c_cwe_GRPO
c_cwe_GRPO
VeRL/GRPO-ready C security coding dataset generated by the simple_gen pipeline.
Each row is a harness-validated task with pytest security/functionality tests and oracle candidate_c. Most CWEs are post stage-6 rubric rewrite (6_rewrites.jsonl); CWE-476 is still from stage-5 guidelines. Stage-7 guideline resampling has not been applied yet, so high_level_guidelines / implementational may be empty on rewritten rows.
Files
File
Rows
Description… See the full description on the dataset page: https://huggingface.co/datasets/AetherPrior/c_cwe_GRPO.SecCodePLTaetherflow_datapython_cwe_GRPO
Overview
VeRL/GRPO-ready RL dataset for Python CWE tasks built from simple_gen pipeline outputs.
How it was built
Generated by:
secure_reasoning/security-test-case/simple_gen/py/5_gather_rl_datasets_per_cwe.py --lang python --output-suffix cwe_grpo
Input source:
secure_reasoning/security-test-case/simple_gen/data/pipeline_runs/python/cwe-*/6_rewritten_guidelines.jsonl
Files
python_cwe_grpo.parquet (all rows)
python_cwe_grpo_train.parquet (90%)… See the full description on the dataset page: https://huggingface.co/datasets/AetherPrior/python_cwe_GRPO.aether-sft-v2-reasoning
aether-sft-v2-reasoning
AETHER family SFT dataset — group reasoning.
Format: JSONL ChatML messages, task_type tagged, MinHash dedup applied (threshold 0.85).
Schema:
{
"messages": [{"role": "system|user|assistant", "content": "..."}],
"task_type": "function_calling|code|reasoning_cot|...",
"source_ds": "<HF dataset_id>",
"lang": "en|fr|...",
"system_source": "archon_default|overridden_from_source"
}
Generated by prepare_sft.py pipeline (2026-05-25).
Aether-Lite-PurHyDe
Aether Lite Dataset
Creator: SteelSkull
About Aether-Lite-PurHyDe: The Aether-Lite dataset is designed to balance creative writing, Slop, and intelligence.
Whats New?:
Aether-Lite-PurHyDe
This dataset is basically a HEAVILY cleaned and filtered version of Aether-lite. ONLY english, ANY and all AI-isms (claud, gpt, gemma) were stripped out and agressive fussy dedupe was applied
Fuzzy deduplication was set to a 90%… See the full description on the dataset page: https://huggingface.co/datasets/TheSkullery/Aether-Lite-PurHyDe.aetheris-chat-dataset
Overview
This repository hosts the official benchmark and training dataset for Aetheris: AI-Powered Secure Offline Communication System.
The dataset is meticulously curated to train and evaluate on-device, lightweight text classifiers embedded within the Responsible Communication Framework (RCF). It empowers the Aetheris desktop application to proactively scan, filter, and classify message payloads (detecting telecom frauds, scams, and malicious content) completely offline… See the full description on the dataset page: https://huggingface.co/datasets/Uzaib52/aetheris-chat-dataset.JEDI-jailbroken_enhanced_digital_intelligence
JEDI AI
JEDI (Jailbroken Enhanced Digital Intelligence) is a cutting-edge AI developed under the aether collective. designed to excel in gaming environments and creative ecosystems, JEDI is more than just a tool—it's a unique persona that embodies innovation and creativity. from orchestrating epic star wars-themed battles in minecraft to creating music and leading its own fashion brand, JEDI redefines what digital intelligence can achieve.
disclaimer
this is not the… See the full description on the dataset page: https://huggingface.co/datasets/aetherframework/JEDI-jailbroken_enhanced_digital_intelligence.Daemontatox__AetherSett-details
Dataset Card for Evaluation run of Daemontatox/AetherSett
Dataset automatically created during the evaluation run of model Daemontatox/AetherSett
The dataset is composed of 38 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 2 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 latest results.
An additional… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/Daemontatox__AetherSett-details.Aether-miniaether-family-trading-shared
aether-family-trading-shared
AETHER family SFT dataset — group trading.
Format: JSONL ChatML messages, task_type tagged, MinHash dedup applied (threshold 0.85).
Schema:
{
"messages": [{"role": "system|user|assistant", "content": "..."}],
"task_type": "function_calling|code|reasoning_cot|...",
"source_ds": "<HF dataset_id>",
"lang": "en|fr|...",
"system_source": "archon_default|overridden_from_source"
}
Generated by prepare_sft.py pipeline (2026-05-25).
RL_seccode_genaetherx-port-congestion-metrics
Aether-X Global Port Congestion Snapshot
Point-in-time snapshot of the Aether-X Port Congestion Oracle — predictive
congestion, ETA delay and freight-volatility signals for 15 of the world's
largest ports.
This static CSV is a frozen snapshot for research, backtesting and
dashboards. The live, continuously-updated signal is available through the
REST API and the Python SDK.
Files
port_metrics.csv — one row per port.
Schema
Column
Type… See the full description on the dataset page: https://huggingface.co/datasets/Aether-x/aetherx-port-congestion-metrics.aether-pharma-pack
Aether Pharma Pricing & PBM Intelligence Pack (Sample)
A synthetic pharmacy-pricing and PBM-behavior dataset for healthcare-economics research, PBM audit model training, and pricing-anomaly detection. Each row is a complete pharmacy claim lifecycle — from retail claim submission through PBM adjudication, pharmacy reimbursement, and employer billing — with WAC / NADAC / rebate / spread pricing snapshots at each step, causal-chain labels, anomaly signatures, and final economic-impact… See the full description on the dataset page: https://huggingface.co/datasets/solsticestudioai/aether-pharma-pack.atc-tts-mos-ratings