datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
multimodal_data_annotator_datasetMaterials dataset consisting of spatial and time resolved versions of the same object. Specially curated for the annotator such that for each object, time resolved signal may be viewed alongside the RGB and for different graphs/forms
annotators
Genomic Variant Annotators
Curated genomic variant annotation modules from the DNA-seq project.
Overview
This dataset contains pre-computed annotation data for genetic variants, organized by module:
Module
Description
Files
longevitymap
Longevity-associated variants
annotations.parquet, studies.parquet, weights.parquet
Schema
annotations.parquet
Variant-level facts linking rsIDs to genes and phenotypes.
rsid: dbSNP… See the full description on the dataset page: https://huggingface.co/datasets/just-dna-seq/annotators.robogaze-annotator-videosukr-emotions-per-annotator
EmoBench-UA: Emotions Detection Dataset in Ukrainian Texts
EmoBench-UA: the first of its kind emotions detection dataset in Ukrainian texts. This dataset covers the detection of basic emotions: Joy, Anger, Fear, Disgust, Surprise, Sadness, or None.
Any text can contain any amount of emotion -- only one, several, or none at all. The texts with None emotions are the ones where the labels per emotions classes are 0.
Per annotator: specifically this dataset contains concatenated… See the full description on the dataset page: https://huggingface.co/datasets/ukr-detect/ukr-emotions-per-annotator.asset-annotator-storeannotator-9-11-explicit-rating-data-vocalsannotator-9-11-explicit-rating-dataauditkit-testrun-annotators
auditkit-testrun-annotators
Built using AuditKIT — evaluate any model on any dataset and any task.
Method
evaluate
Model
<auditkit.model.vllm_gen.VLLMModel object at 0x79713e2dacf0>
Artifact
run
Published
2026-09-02 04:38 UTC
Usage
from datasets import load_dataset
ds = load_dataset("ram-lexsi/auditkit-testrun-annotators")
baidu-ultr-user-annotator-agreementgoldenswag-fi-annotator-10test_custom_annotator
test_custom_annotator
Custom simple extraction from reasoning traces
Dataset Info
Rows: 1
Columns: 24
Columns
Column
Type
Description
question
Value('string')
No description provided
metadata
Value('string')
No description provided
task_source
Value('string')
No description provided
formatted_prompt
List({'content': Value('string'), 'role': Value('string')})
No description provided
responses_by_sample
List(List(Value('string')))
No… See the full description on the dataset page: https://huggingface.co/datasets/reasoning-degeneration-dev/test_custom_annotator.MedSynth-1perICD10-annotator-1goldenswag-fi-og-annotator-10goldenswag-fi-annotator-1goldenswag-fi-og-annotator-1goldenswag-fi-og-annotator-9MedSynth-1perICD10-annotator-6MedSynth-1perICD10-annotator-9presuisidal_dataset-test_split-three_annotatorsMedSynth-1perICD10-annotator-4MedSynth-1perICD10-annotator-5MedSynth-1perICD10-annotator-7ArabicaQA_retriever_train_data_human_annotator_70kgoldenswag-fi-annotator-9MedSynth-1perICD10-annotator-3budgetforce_training_examples__base__Annotator_qwen2.5-1.5B-InstructMedSynth-1perICD10-annotator-2MedSynth-1perICD10-annotator-8MedSynth-1perICD10-annotator-0highlight-annotator-2608-refine