datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Mercury_MultilingualMercury
Welcome to Mercury 🪐!
This is the dataset of the paper 📃 Mercury: A Code Efficiency Benchmark for Code Large Language Models
Mercury is the first code efficiency benchmark designed for code synthesis tasks.
It consists of 1,889 programming tasks covering diverse difficulty levels, along with test case generators that produce unlimited cases for comprehensive evaluation.
How to use Mercury Evaluation
git clone https://github.com/Elfsong/Mercury_Eval.git
cd… See the full description on the dataset page: https://huggingface.co/datasets/Elfsong/Mercury.PyInstruct PyBench: Evaluate LLM Agent on Real World Tasks
📃 Paper
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🤗 Data (PyInstruct)
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🤗 Model (PyLlama3)
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Code
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PyBench is a comprehensive benchmark evaluating LLM on real-world coding tasks including chart analysis, text analysis, image/ audio editing, complex math and software/website development. We collect files from Kaggle, arXiv, and other sources and automatically generate queries according to the type and content of each file.
Why PyBench?
The LLM Agent, equipped… See the full description on the dataset page: https://huggingface.co/datasets/Mercury7353/PyInstruct.mercury_verl
Mercury (verl efficiency eval set)
The eval split of Elfsong/Mercury
(arXiv 2402.07844; 256 LeetCode-style tasks;
the train split ships no test cases and is not gradable), converted to the verl
rule-reward schema by verl/scripts/data/mercury.py. Source license
CC-BY-NC-4.0 (non-commercial) -- this conversion keeps that license.
Every row's ground truth carries the full official scoring contract: entry
point, the task's convert_offline/evaluate_offline hooks (lctk linked-list /… See the full description on the dataset page: https://huggingface.co/datasets/OctoReasoner/mercury_verl.africa-synth-mental-health-mercury-exposure-asgm-all
Mercury Exposure & Artisanal Gold Mining (SSA) | Africa (Electric Sheep Africa metadata inventory)
Size category: 10K<n<100K - Formats: csv - Sector: health - Engineered by Electric Sheep Africa
TL;DR
This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.
What This Dataset Covers
Health… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-synth-mental-health-mercury-exposure-asgm-all.Mercury-Thermometer-Temperature-Classification-Dataset-in-Home-Scenarios
Mercury Thermometer Temperature Classification Dataset in Home Scenarios
In the current medical industry, home care and health monitoring are increasingly emphasized, especially since the accuracy of temperature monitoring directly affects the early diagnosis and treatment of diseases. However, due to users' different understanding of how to use thermometers, the reliability of measurement results has been insufficient. Existing solutions rely heavily on manual annotation and… See the full description on the dataset page: https://huggingface.co/datasets/Mobiusi/Mercury-Thermometer-Temperature-Classification-Dataset-in-Home-Scenarios.mercury-craters-herrick
Mercury Crater Database (Herrick et al. 2011)
Credit: NASA/Apollo 8
Part of the Planetary Science Datasets collection on Hugging Face.
The global Mercury impact crater database containing 16,876 craters identified from Mariner 10 and MESSENGER flyby imagery. This catalog provides the most complete inventory of Mercury's cratered surface, with morphological classifications for interior shape, rim geometry, and central structures.
Dataset description
This database… See the full description on the dataset page: https://huggingface.co/datasets/juliensimon/mercury-craters-herrick.mercury-crater-degradation
Mercury Crater Degradation (Kinczyk et al. 2020)
Credit: NASA/Apollo 8
Part of the Planetary Science Datasets collection on Hugging Face.
A global catalog of 3,253 Mercury impact craters (diameter >= 40 km) classified by morphological degradation state using MESSENGER imagery. Each crater is assigned a degradation class from 1 (freshest) to 5 (highly degraded), providing a relative chronology of Mercury's surface.
Dataset description
Crater degradation is the… See the full description on the dataset page: https://huggingface.co/datasets/juliensimon/mercury-crater-degradation.Mercury-Thermometer-Damage-and-Crack-Detection-Image-Dataset
Mercury Thermometer Damage and Crack Detection Image Dataset
The current medical industry faces numerous challenges in equipment monitoring and safety checks, especially in the use of mercury thermometers, where damage and cracks can pose serious safety hazards. Existing detection solutions often rely on manual inspection, which is not only inefficient but also prone to missed detections and misjudgments. Therefore, constructing a high-quality mercury thermometer damage and crack… See the full description on the dataset page: https://huggingface.co/datasets/Mobiusi/Mercury-Thermometer-Damage-and-Crack-Detection-Image-Dataset.Mercury_CDS
Dataset Card for "Mercury_CDS"
More Information needed
mercury
Mercury Planet Facts Dataset
This dataset contains multilingual facts about the planet Mercury, provided in Indonesian, English, Spanish, and German.
📄 License
This dataset is released under the Apache License 2.0.It is free to use for research, commercial, educational, and personal purposes — with appropriate attribution.
🏢 Source
This dataset was developed and published by Eris Dataworks, a data engineering company providing high-quality datasets to… See the full description on the dataset page: https://huggingface.co/datasets/erisdataworks/mercury.autophagycode_D_he_train-mercury_Qwen3-8B_strategy_surplexity_t1_g8_run2_metricsautophagy_D_mercuryautophagycode_D_mercury_Qwen3-8B_t1.0_g5_run2autophagycode_D_mercury_Qwen3-8B_lr0.0001_c142_surplexity_t0.2_g1_run2beaver-dw-plan-sql
BEAVER-dw Plan→SQL
A restructuring of the dw subset of BEAVER
into a plan-then-SQL format, with family-disjoint splits.
Each example asks a model to emit a structured plan first and the SQL second:
{
"question": "Which departments offered the most subjects last term?",
"domain_knowledge": ["..."],
"ir": {
"tables": ["SIS_DEPARTMENT", "SUBJECT_OFFERED_SUMMARY"],
"join_keys": [{"left": "SIS_DEPARTMENT.DEPARTMENT_CODE",
"right":… See the full description on the dataset page: https://huggingface.co/datasets/mercurylabs-ai/beaver-dw-plan-sql.DreadPoor__Mercury_In_Retrograde-8b-Model-Stock-details
Dataset Card for Evaluation run of DreadPoor/Mercury_In_Retrograde-8b-Model-Stock
Dataset automatically created during the evaluation run of model DreadPoor/Mercury_In_Retrograde-8b-Model-Stock
The dataset is composed of 38 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 1 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… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/DreadPoor__Mercury_In_Retrograde-8b-Model-Stock-details.autophagycode_D_he_train-mercury_Qwen3-8B_strategy_surplexity_t0.2_g1_run1autophagycode_D_mercury_Qwen3-4B_t0.5_g0_run2yolo_val2017autophagycode_D_mercury_Qwen3-4B_t0.5_g7_run1autophagycode_D_mercury_Qwen3-4B_lr0.0001_c142_surplexity_t1_g6_run1autophagycode_D_he_train-mercury_Qwen3-8B_strategy_surplexity_t0.2_g5_run1autophagycode_D_mercury_Qwen3-4B_t0.5_g6_run2autophagycode_D_mercury_Qwen3-4B_t0.75_g0_run0autophagycode_D_mercury_Qwen3-4B_t0.75_g1_run0autophagycode_D_he_train-mercury_Qwen3-4B_strategy_surplexity_t1_g9_run1_metricsautophagycode_D_he_train-mercury_Qwen3-8B_strategy_surplexity_t0.2_g8_run1autophagycode_D_mercury_Qwen3-8B_lr0.0001_c142_surplexity_t0.2_g7_run2autophagycode_D_mercury_Qwen3-4B_t1.0_g9_run0