datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
pile_pythonmega-precision-image-video
Mega Precision Image & Video Dataset
Description
A high-quality dataset for training image and video generation models with ultra-detailed prompts, technical parameters, and quality metrics.
Content
10,000,000 examples
4 categories: image prompts, video prompts, technical parameters, quality metrics
English language
Categories
Category
Description
%
Image Prompts
Ultra-detailed prompts for image generation
30%
Video… See the full description on the dataset page: https://huggingface.co/datasets/Lelonthecodeur/mega-precision-image-video.Log_precisionprecision-evidence-bench
Precision Evidence Bench
Precision Evidence Bench is a Precision Medicine Benchmark from
Atropos Health, the world's largest creator of
real-world evidence (RWE) for clinical decision support. It evaluates how well
large language models (LLMs) answer clinical questions that are grounded in
patient context and inclusive of patient history: not "which treatment is
better in general", but "which treatment is better for this patient", with a
specific comorbidity, age, prior therapy… See the full description on the dataset page: https://huggingface.co/datasets/atroposhealth/precision-evidence-bench.pile_cppprecisionmembenchPrecisionMemBench is a multi-dimensional retrieval benchmark for LLM memory systems. It measures four orthogonal properties that single-turn answer-quality benchmarks cannot detect:
Retrieval precision - does the right belief surface, and only that belief, against a fixed seed corpus of 35 beliefs spanning two domain scopes, a supersession chain, and a secondary-user fixture
Noise isolation - do beliefs introduced during off-topic drift turns contaminate retrieval on subsequent unrelated… See the full description on the dataset page: https://huggingface.co/datasets/tenurehq/precisionmembench.hedgehog-precision-repair
hedgehog-precision-repair
Hedgehog — precision-repair round (complete merchant extraction).
Contents
train.jsonl (1180 rows)
validation.jsonl (116 rows)
Format
JSON Lines (.jsonl), one example per line.
Provenance
Original content for the Hedgehog extraction model (Michael Anthony Falabella).
llm-precision-fingerprints
LLM Precision Fingerprints — precision-labelled logprobs with a built-in negative control
Greedy responses and per-position top-20 logprobs from one model served at several precisions over
a sealed 40-probe set, recorded on identical hardware.
What makes this different from any other logprob dump: it ships five fp16 arms that differ
only in seed and batch composition. Those are a negative control — they let you compute the
false-positive rate of any substitution detector you… See the full description on the dataset page: https://huggingface.co/datasets/nickh007/llm-precision-fingerprints.Synthetic-Data-for-Precision-Gauge-Reading
Dataset Card for Dataset Name
This dataset card aims to be a base template for new datasets. It has been generated using this raw template.
Dataset Details
Dataset Description
Curated by: [More Information Needed]
Funded by [optional]: [More Information Needed]
Shared by [optional]: [More Information Needed]
Language(s) (NLP): [More Information Needed]
License: [More Information Needed]
Dataset Sources [optional]
Repository: [More… See the full description on the dataset page: https://huggingface.co/datasets/KhoaUIT/Synthetic-Data-for-Precision-Gauge-Reading.TREC_Precision-Medicine
TREC Precision Medicine (2017, 2018 and 2019)
Links
Homepage:
TREC
Paper:
2017 / 2018 / 2019 / 2020
Contact (Original Authors):
Kirk Roberts (Kirk.Roberts@uth.tmc.edu )
Contact (Curator):
Artur Guimarães (artur.guimas@gmail.com)
Dataset Summary
This track focused on oncologists looking for evidence-based treatment literature and clinical trials.
Data Instances
Source Format
{
"query_id":"1",
"disease":"melanoma"… See the full description on the dataset page: https://huggingface.co/datasets/araag2/TREC_Precision-Medicine.africa-synth-agriculture-precision-iot-nigeria
Africa Synth Agriculture Precision Iot Nigeria | Africa (Electric Sheep Africa metadata inventory)
Size category: 10K<n<100K - Formats: parquet - Sector: agriculture_food - 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… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-synth-agriculture-precision-iot-nigeria.faithfulness-precision-spl-context-gpt-benchmarkingadaption-precision-agriculture-qa-augmented
This dataset is a remastered version prepared using Adaption's Adaptive Data platform.
adaption-precision_agriculture_qa (augmented)
This dataset consists of instruction and response pairs focused on precision agriculture technologies and methodologies. Queries cover topics such as soil sensor integration, variable rate application, yield mapping, and data-driven farm management. Each response provides detailed technical explanations and operational guidance for optimizing… See the full description on the dataset page: https://huggingface.co/datasets/darthludious/adaption-precision-agriculture-qa-augmented.context-precision-ragasllm-stop-point-precision
license: cc-by-4.0
language:
en
---Title
Stop-Point Precision Evaluation for LLMs
Summary
This dataset captures stop-point precision failures in large language models. It focuses on cases where a response is correct but should have terminated earlier, violating explicit constraints such as word count, sentence count, or binary-only answers.
What this dataset tests
• Whether a model knows when to stop
• Adherence to explicit response boundaries
• Overcompletion after correct answers
Why this… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/llm-stop-point-precision.math_precision_benchmarking
🧮 Math Precision — Benchmarking
A Formal Framework for High-Precision Arithmetic Evaluation in Large Language Models
Math Precision — Benchmarking, developed by Sapiens Technology®, is a rigorous framework for evaluating the true arithmetic capabilities of large language models by generating fully stochastic, high-precision mathematical problems that eliminate memorization and heuristic guessing; operating in a 100-digit floating-point field, it forces extreme numerical precision… See the full description on the dataset page: https://huggingface.co/datasets/sapiens-technology/math_precision_benchmarking.kanitakorn-thaiexam-v29-thai-language-precision-worker-e-20260614fnbm-current-gt-motif-effects-precision-20260729
fnbm-current-gt-motif-effects-precision-20260729
Recovery of planted motif effects after de-duplication, scored against simulation ground truth. Effect sizes are the OLS slope of each motif family's post-clustering per-example contribution on the motif's true occurrence count -- the same units as the simulator's beta, and invariant to the de-duplication pipeline's internal gauge. Per-example contribution MSE is computed on centered contributions over the validation split. See… See the full description on the dataset page: https://huggingface.co/datasets/arushram/fnbm-current-gt-motif-effects-precision-20260729.BrainStorm2026-track2pile_jsgsm8k-question-precision-levels
GSM8K Question Precision Levels
198 GSM8K problems, each stated at three levels of question precision, all
sharing one correct answer.
Field
Meaning
level_2
Original GSM8K question, unchanged
level_1
level_2 with exactly one span removed from the question sentence
level_0
A short model-written rewrite of the task
answer
Numeric ground truth, the same for all three levels
solution
Original GSM8K worked solution
removal_type
Which kind of removal produced… See the full description on the dataset page: https://huggingface.co/datasets/busycaesar/gsm8k-question-precision-levels.kilo_code_precision_training_datafaithfulness-precision-spl-prompt-gpt-benchmarkingswamiji-vae-precision-reviewsia_pile_sampleprecision_agriculture_soil_health_monitoringPrecision-Crop-Genomics-lane-state
Precision-Crop-Genomics — lane-state mirror
Public mirror of the Precision-Crop-Genomics lane's product-page bundle and
orchestration state. This dataset is the redundant-storage backup of the lane
work; the canonical source of truth is the GitHub lane repo.
Canonical source
GitHub (canonical): https://github.com/Zer0pa/Precision-Crop-Genomics
GitHub branch holding this bundle:
lane-agent/showcase-product-page-2026-05-12
GitHub commit at upload time: 0ffe5843cb71… See the full description on the dataset page: https://huggingface.co/datasets/Zer0pa/Precision-Crop-Genomics-lane-state.faithfulness-precision-spl-prompt-falcon-benchmarkingsanity-test-precision-rlprecision_medicine_genomic_drug_response