datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
co2_energy_dataENERGY_DATAenergy-attested-runs
Part of the SZL Holdings governed estate — claims are designed to carry checkable receipts. Verification proves integrity & origin, never accuracy or performance.
Energy-Attested Inference Runs - 8 signed mock-route receipts; energy unavailable
Append-only sample receipts produced by the live
Space SZLHOLDINGS/energy-attested-runs.
Snapshot truth - independently audited 2026-07-15: this release contains
exactly 8/8 cryptographically valid ECDSA-P256… See the full description on the dataset page: https://huggingface.co/datasets/SZLHOLDINGS/energy-attested-runs.chinese-clean-energy-battery-open-intelligence
🔬 Chinese Clean Energy, Battery Chemistry & Smart Grid Open Intelligence Dataset
Curated open intelligence dataset tracking authentic Chinese scientific breakthroughs in Solid-State Battery chemistry, Perovskite Solar cells, Ultra-High Voltage (UHV) power grids, and industrial decarbonization.
[!IMPORTANT]
Data Completeness & Research Authenticity Notice:
Included in this Hugging Face Open Dataset: English structured abstracts, core quantitative takeaways, author… See the full description on the dataset page: https://huggingface.co/datasets/simpleG2023/chinese-clean-energy-battery-open-intelligence.IEA_Energy_Dataset
IEA_Energy_Dataset
Dataset Details
Dataset Description
The dataset is energy-related, covering topics of Oil, Coal, Wind, Hydrogen, Bioenergy, Electric vehicles, Heating, Building envelopes, Methane abatement and Chemicals.
Dataset Creation
Source Data
The dataset sources are reports from the webiste of International Energy Agency(IEA).
Data Collection and Processing
We scraped free open reports from IEA's website. The reports… See the full description on the dataset page: https://huggingface.co/datasets/Zihao-Li/IEA_Energy_Dataset.ai-energy-2026
AI Energy & Environment 2026
Data center power, carbon, water usage. Updated daily via automated collection pipeline.
Part of the Legion Data Factory — historical AI ecosystem datasets 2026.
Methodology
Automated collection from public sources (HackerNews, RSS feeds, APIs).
Updated daily via cron job. Raw data, minimal processing.
License
CC BY 4.0
📦 Install
pip install legion-intel
from legion_intel import LegionClient
c =… See the full description on the dataset page: https://huggingface.co/datasets/gemmozero/ai-energy-2026.ai-compute-energy-2026
AI Compute & Energy 2026
AI compute costs, energy consumption. Updated daily via automated collection pipeline.
Part of the Legion Data Factory — historical AI ecosystem datasets 2026.
Methodology
Automated collection from public sources (HackerNews, RSS feeds, APIs).
Updated daily via cron job. Raw data, minimal processing.
License
CC BY 4.0
📦 Install
pip install legion-intel
from legion_intel import LegionClient
c =… See the full description on the dataset page: https://huggingface.co/datasets/gemmozero/ai-compute-energy-2026.eagle3-speculative-decoding-energy-sweep
EAGLE3 Speculative Decoding Energy Sweep
Per-config energy/throughput/latency measurements for EAGLE3 speculative decoding
(speculative_num_steps, speculative_eagle_topk, speculative_num_draft_tokens)
served with sglang, across batch sizes. Collected for an RL project that learns to
pick speculative-decoding parameters to hold GPU energy utilization in a target band.
Model: unsloth/Llama-3.2-1B-Instruct + rescommons/SpecForge-EAGLE3-Llama-3.2-1B-Instruct draft head.
Hardware:… See the full description on the dataset page: https://huggingface.co/datasets/Pradheep1647/eagle3-speculative-decoding-energy-sweep.energy-code-adoption-by-state
Which energy code each US state enforces for new homes: the IECC edition (or state equivalent) actually in force, with effective dates and amendments, from the state rules themselves
Canonical, always-current version: https://referencesource.org/energy-code-adoption-by-state/
Machine-readable: https://referencesource.org/energy-code-adoption-by-state/data.json — this mirror is a point-in-time copy.
Last verified: 2026-08-18
Stale after: 2027-02-14 (past this date, prefer the… See the full description on the dataset page: https://huggingface.co/datasets/referencesource/energy-code-adoption-by-state.open-telco-energy-logs
Open-Telco Energy Logs
Per-model GPU energy measurements for 67 open-weight LLMs evaluated on the Open Telco benchmark suite. This is the raw data backing the energy and AMEI (AI Model Energy Index) tables in the AMEI paper.
Three measurement campaigns are included:
Campaign
Models
Hardware
Runtime
Suite
Samples/model
Schema
single_h100/
24
1×H100-80GB SXM
vLLM 0.8.5 (TP=1)
open_telco_5_benchmarks
1,400
v1.0
4x_h100/
35
4×H100-80GB SXM
vLLM 0.15.1 (TP=4)… See the full description on the dataset page: https://huggingface.co/datasets/emolero/open-telco-energy-logs.nutritrack-200-meal-reference-suite
🥗 NutriTrack: 200-Meal International Reference Benchmark & Generalization Suite
The NutriTrack-200-International-Reference-Suite is a standardized, lab-calibrated evaluation dataset and active-learning test suite for automated dietary assessment and multimodal food recognition systems.
📊 Dataset Summary
Total Benchmark Meals: 200 reference meals with ground-truth nutritional deconstruction.
Held-Out Active Learning Test Set: 50 distinct, unseen meals for… See the full description on the dataset page: https://huggingface.co/datasets/EnergyVenom/nutritrack-200-meal-reference-suite.ai-energy-prices-2026building-energy-benchmarking-requirements
Building Energy Benchmarking and Performance Standard Requirements by Jurisdiction
Canonical, always-current version: https://referencesource.org/building-energy-benchmarking-requirements/
Machine-readable: https://referencesource.org/building-energy-benchmarking-requirements/data.json — this mirror is a point-in-time copy.
Last verified: 2026-08-15
Stale after: 2027-02-11 (past this date, prefer the canonical copy —
it re-verifies on a cadence this snapshot does not)
Records:… See the full description on the dataset page: https://huggingface.co/datasets/referencesource/building-energy-benchmarking-requirements.home-energy-rebate-program-status-by-state
Home Energy Rebates — is my state's programme open, and what does it still pay for?
Canonical, always-current version: https://referencesource.org/home-energy-rebate-program-status-by-state/
Machine-readable: https://referencesource.org/home-energy-rebate-program-status-by-state/data.json — this mirror is a point-in-time copy.
Last verified: 2026-08-25
Stale after: 2026-09-24 (past this date, prefer the canonical copy —
it re-verifies on a cadence this snapshot does not)… See the full description on the dataset page: https://huggingface.co/datasets/referencesource/home-energy-rebate-program-status-by-state.Renewable_Energy_25k
RenewableEnergy_Archon_25k (Master Scholar)
Developer / Brand: Within Us AI
RenewableEnergy_Archon_25k is a 25,000-example dataset built to train models toward master-scholar capability in renewable energy engineering, systems, and policy:
Solar PV (yield modeling, inverter sizing, temperature effects)
Wind energy (aerodynamic power, capacity factors, wake losses)
Hydropower & pumped hydro (power, storage duration, ecology)
Geothermal (thermal-to-electric estimation, EGS risk… See the full description on the dataset page: https://huggingface.co/datasets/WithinUsAI/Renewable_Energy_25k.ARC-Bind-Energy
ARC-Bind Energy Prediction
Overview
ARC-Bind is a synthetic 2D binding dataset designed to study how machine learning models learn to predict molecular interactions. The goal is to understand model reasoning about binding in a setting small enough to fully inspect and debug.
Inspiration: ARC-AGI Format
Inspired by François Chollet's ARC-AGI benchmark, ARC-Bind uses 16×16 pixel grids with discrete color tokens to represent binding:
Protein: Light blue (token 8)… See the full description on the dataset page: https://huggingface.co/datasets/Leash-Biosciences/ARC-Bind-Energy.adaption-energy-and-carbon-qaThis dataset is a remastered version prepared using Adaption's Adaptive Data platform.
adaption-energy_and_carbon_qa
This dataset contains question-answer pairs derived from time-series charts tracking electricity demand and carbon intensity across various countries. The prompts present chart metadata and plotted values, requiring the model to perform data extraction, comparison, or trend analysis. Responses demonstrate accurate interpretation of specific data points… See the full description on the dataset page: https://huggingface.co/datasets/rodriguescarson/adaption-energy-and-carbon-qa.han-humanoid-energy-consumption-records-v1
Humanoid Energy Consumption Records (HECR)
Problem Definition
Energy efficiency is a key factor in industrial humanoid deployment.
This dataset captures execution parameters
and corresponding energy consumption metrics.
Features
task_type
payload_weight
movement_speed
torque_average
execution_time
ambient_temperature
Target
energy_consumption_kwh (float)
Use Cases
Energy prediction
Efficiency optimization
Cost reduction modeling… See the full description on the dataset page: https://huggingface.co/datasets/ariefansclub/han-humanoid-energy-consumption-records-v1.ai-energy-futures-2026Energy_LLM_Wikismart-home-energy-gemma3
Smart Home Energy Optimization Dataset (Bilingual - FR/EN)
This dataset is designed for fine-tuning lightweight language models (e.g., Gemma 1B) for local energy assistant use cases in smart homes.It contains synthetic instruction-response pairs in both French and English, ideal for on-device LLMs running on resource-constrained environments like a Raspberry Pi 4 (4GB RAM).
💡 Use Case
Smart Home Energy Assistant:An on-device assistant that helps users reduce energy… See the full description on the dataset page: https://huggingface.co/datasets/Epitech/smart-home-energy-gemma3.time_series_energyeseu-wmt26-energy-devnutritrack-200-benchmark
🥗 NutriTrack: 200-Meal International Reference Benchmark & Generalization Suite
The NutriTrack-200-International-Reference-Suite is a standardized, lab-calibrated evaluation dataset and active-learning test suite for automated dietary assessment and multimodal food recognition systems.
## 📊 Dataset Summary
* Total Benchmark Meals: 200 reference meals with ground-truth nutritional deconstruction.
* Held-Out Active Learning Test Set: 50 distinct, unseen meals for… See the full description on the dataset page: https://huggingface.co/datasets/EnergyVenom/nutritrack-200-benchmark.han-humanoid-energy-efficiency-v1
Humanoid Energy Efficiency Dataset (HEED)
Description
This dataset records energy consumption metrics
for humanoid robots during repetitive task execution.
Features
task_type
payload_kg
speed_m_s
torque_index
execution_time_s
energy_kwh
Target
energy_kwh
Use Cases
Energy consumption prediction
Cost optimization
Efficiency modeling
Evaluation Metrics
MAE
RMSE
License
MIT
thorium_nuclear_energy_qa_squad
Thorium Nuclear Energy Q&A Dataset
Dataset Summary
The Thorium Nuclear Energy Q&A Dataset is a manually curated collection of 111 question-answer pairs related to thorium-based nuclear energy. The data is formatted in SQuAD 2.0 JSON style and is designed to support reading comprehension, domain-specific QA research, and educational tools. Topics span technical, historical, economic, environmental, and geopolitical aspects of thorium energy.
Dataset Structure… See the full description on the dataset page: https://huggingface.co/datasets/itsarnf/thorium_nuclear_energy_qa_squad.eseu-wmt26-energy-syntheticenergy_ZSKhumanoid-energy-management-tr-v1Energy efficiency interaction dataset for humanoid robots.
Description
Basic household energy monitoring and optimization interactions.
Task Description
Teaches humanoid robots to monitor electricity usage, disable idle devices and activate energy-saving modes in indoor environments.
han-humanoid-energy-consumption-logs-v1
Humanoid Energy Consumption Logs
Overview
This dataset captures energy usage
metrics during humanoid task execution.
It supports research in power efficiency
and sustainable robotics deployment.
Data Fields
task_name
battery_level_start
battery_level_end
energy_consumption_percentage
recharge_required
Intended Use
Energy optimization modeling
Resource management research
Autonomous charging systems
License
MIT