datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
deval_helm_hyperturing1boolq_helmHELMET
HELMET: How to Evaluate Long-context Language Models Effectively and Thoroughly
[Paper][Code]
HELMET is a comprehensive benchmark for long-context language models covering seven diverse categories of tasks.
The datasets are application-centric and are designed to evaluate models at different lengths and levels of complexity.
Please check out the paper for more details, and the code repo for how to process the data and run the evaluations
Safety-helmet-datasetSafety-helmet-datasetstack-v3-devops
The Stack v3 DevOps Corpus
13,234,862 complete infrastructure units extracted from
The Stack v3,
grouped into seven classes and gated on content rather than popularity.
A unit is not a file, it is the thing an engineer would actually run: a Helm chart
arrives with its Chart.yaml, values.yaml and every template; a Terraform module
with all of its .tf files; an Ansible role with its tasks, defaults and handlers.
That is only possible because The Stack v3 groups rows by repository… See the full description on the dataset page: https://huggingface.co/datasets/Helmcode/stack-v3-devops.bigbench_helmtruthfulqa_helm
Dataset Card for "truthfulqa_helm"
More Information needed
helmholtz_staircaseThis Dataset is part of The Well Collection.
How To Load from HuggingFace Hub
Be sure to have the_well installed (pip install the_well)
Use the WellDataModule to retrieve data as follows:
from the_well.benchmark.data import WellDataModule
# The following line may take a couple of minutes to instantiate the datamodule
datamodule = WellDataModule(
"hf://datasets/polymathic-ai/",
"helmholtz_staircase",
)
train_dataloader = datamodule.train_dataloader()
for batch in… See the full description on the dataset page: https://huggingface.co/datasets/polymathic-ai/helmholtz_staircase.helm-scenarios
HELM Scenarios
This repository contains mirrors of datasets that are used as scenarios by crfm-helm.
Scenarios
TURL Column Type Annotation
The subfolder turl-column-type-annotation contains files for the table column type annotation task from the TURL paper. No modifications were made to these files.
The TURL dataset by Xiang Deng, Huan Sun, Alyssa Lees, You Wu, and Cong Yu is licensed under CC BY 4.0. The TURL dataset was modified from the TabEL… See the full description on the dataset page: https://huggingface.co/datasets/stanford-crfm/helm-scenarios.HELM-Easiness-Data-10B-Labeled-v6HELM-Easiness-Data-10B-Labeled-v5bike-helmet-dataset
Bike Helmet Detection Dataset
This repository contains multiple computer vision datasets for bike helmet detection.
1. Bike Helmet Detection (COCO Format)
Location: Root folders (train/, valid/, test/)
Total Images: 1376
Splits:
train/: 1185 images and _annotations.coco.json
valid/: 127 images and _annotations.coco.json
test/: 64 images and _annotations.coco.json
Format: COCO
2. Bikes Helmets Dataset (Pascal VOC Format)
Location: helmet_voc/… See the full description on the dataset page: https://huggingface.co/datasets/cute-face/bike-helmet-dataset.HELMET-8192-RAGSafety-helmet-datasetbbq_helmtrain_splits_helmContains the following train split from datasets in helm:
big bench
mmlu
TruthfulQA
cnn/dm
gsm
bbq
boolq
NarrativeQA
QuAC
math
bAbI
Each prompt has <= 5 in-context samples along with a sample, all of which from the train set of the respective datasets.
Safety-helmet-datasetSafety-helmet-datasethelmet-codellava-eval-v2IITU_Safety-Helmet_Dataset_v1.0
IITU Safety-Helmet Dataset v1.0
Overview:
This dataset contains annotated images of safety helmets captured both by drone and at ground level, designed for helmet detection and color classification tasks in computer vision.
📖 Dataset Summary
This dataset contains 1,664 images annotated for safety-helmet detection and color classification.
6,473 helmet instances
Captured by drone (3–5 m, 10–15 m; angles 0°, 45°, 90°) and at ground level… See the full description on the dataset page: https://huggingface.co/datasets/ersace/IITU_Safety-Helmet_Dataset_v1.0.natural_questions_helm
Dataset Card for "natural_questions_helm"
More Information needed
HELMET
HELMET: How to Evaluate Long-context Language Models Effectively and Thoroughly
[Paper][Code]
HELMET is a comprehensive benchmark for long-context language models covering seven diverse categories of tasks.
The datasets are application-centric and are designed to evaluate models at different lengths and levels of complexity.
Please check out the paper for more details, and the code repo for how to process the data and run the evaluations
bike-helmet-dataset
Bike Helmet Detection Dataset
This repository contains multiple computer vision datasets for bike helmet detection.
1. Bike Helmet Detection (COCO Format)
Location: Root folders (train/, valid/, test/)
Total Images: 1376
Splits:
train/: 1185 images and _annotations.coco.json
valid/: 127 images and _annotations.coco.json
test/: 64 images and _annotations.coco.json
Format: COCO
2. Bikes Helmets Dataset (Pascal VOC Format)
Location: helmet_voc/… See the full description on the dataset page: https://huggingface.co/datasets/shravya11/bike-helmet-dataset.copyright_helmreeval-difficulty-for-helmolmes-helmet-fixed-v2
OLMES HELMET Fixed Datasets
Generated from benchmark/HELMET_olmes/dataset_backup/tasks and the
benchmark/visualization review outputs.
Policy:
confirmed rerank qrel bugs are repaired;
deterministic QA replacements are rewritten when supported by context;
confirmed QA/ICL bugs without a deterministic replacement are dropped;
pending QA rows marked needs_fix are dropped;
tokenization-only QA answer surfaces are canonicalized.
These JSONL files are processed OLMES task datasets… See the full description on the dataset page: https://huggingface.co/datasets/sagels/olmes-helmet-fixed-v2.civil_comments_helmpile_helmHelmholtz
Short Description
This dataset comprises solutions of the Helmholtz equation, see https://arxiv.org/abs/2405.19101.
Dimensions
The H5 file has 19675 variables called Sample_i where i is the sample number. Every sample has three sub-groups:
a with dimensionality
128 (x-dim)
128 (y-dim)
bc (the value of the Dirichlet boundary condition, a float), as well as u with dimensionality
128 (x-dim)
128 (y-dim)
Train/Val/Test-split
19035/128/512 trajectories… See the full description on the dataset page: https://huggingface.co/datasets/camlab-ethz/Helmholtz.