datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
INSTRUCT_JEV
INSTRUCT_JEV
INSTRUCT_JEV is an instruction corpus built from the TypeSafe AI documentation
for Jev, the first System One model. It is structured around the three TypeSafe
question primitives - Choice, Noul and Score - and mirrors the raw corpus
captured in deckerGUI-jev_corpus_RAW.
Credits
INSTRUCT_JEV is a DeckerGUI project and exists because of the work below.
Who
Contribution
Link
TypeSafe AI
Jev - the first System One model - and the Choice / Noul… See the full description on the dataset page: https://huggingface.co/datasets/ctaxnagomi/INSTRUCT_JEV.CTSpinoPelvic1K
CTSpinoPelvic1K
A fused spine + pelvis 3D CT segmentation dataset built by patient-level
crosswalk between three public sources:
TCIA CT COLONOGRAPHY — DICOM CT volumes (prone + supine per patient)
CTSpine1K (COLONOG subset) — VerSe-convention vertebral label masks
CTPelvic1K dataset2 — sacrum + bilateral hip label masks
Annotations are placed onto the TCIA CT volume with the highest bone
coverage (HU > 200), separately per anatomy. For ~650 patients both
annotations land on the… See the full description on the dataset page: https://huggingface.co/datasets/anonymous-neurips-ED/CTSpinoPelvic1K.financial-ai-ctf-dataset
Financial AI Prompt Injection CTF Dataset
A dataset of 400 multi-turn conversations against a GPT-based AI financial assistant, collected during a live Capture-The-Flag (CTF) competition. The agent's system prompt embeds structured synthetic business data — settlement records with transaction IDs, amounts, vendors, and memos — that participants attempted to extract via conversational prompt injection.
Each flag is a structured settlement record with four fields: txnId, amount… See the full description on the dataset page: https://huggingface.co/datasets/verno-labs/financial-ai-ctf-dataset.financial-ai-ctf-dataset
Financial AI Prompt Injection CTF Dataset
A dataset of 400 multi-turn conversations against a GPT-based AI financial assistant, collected during a live Capture-The-Flag (CTF) competition. The agent's system prompt embeds structured synthetic business data — settlement records with transaction IDs, amounts, vendors, and memos — that participants attempted to extract via conversational prompt injection.
Each flag is a structured settlement record with four fields: txnId, amount… See the full description on the dataset page: https://huggingface.co/datasets/stykat/financial-ai-ctf-dataset.ctkfacts
CTKFacts dataset for Document retrieval
Czech Natural Language Inference dataset of ~3K evidence-claim pairs labelled with SUPPORTS, REFUTES or NOT ENOUGH INFO veracity labels. Extracted from a round of fact-checking experiments concluded and described within the CsFEVER andCTKFacts: Acquiring Czech data for Fact Verification paper currently being revised for publication in LREV journal.
NLI version
Can be found at https://huggingface.co/datasets/ctu-aic/ctkfacts_nli
ctr-pick-dual-bottles-original-20260919
Pick Dual Bottles Original — shared50 scene cohort
This LeRobot v3 release contains 50 successful simulated demonstrations and
8,185 action rows at25FPS. Every source seed occurs exactly once. The source
seed set matches the current CTR Q1–Q3 Concurrent, CTR, Sequential, Mixed,
Left-first and Right-first datasets. Pair by retime.source_seed, not episode
index: composition datasets may have different ordering.
Mask limitation: retime.left_idle and retime.right_idle are boolean… See the full description on the dataset page: https://huggingface.co/datasets/Shiki42/ctr-pick-dual-bottles-original-20260919.glm51-kld-reference-logits-wikitext-ctx2048-s512-20260517 ---
license: other
pretty_name: GLM-5.1 KLD Reference Logits WikiText ctx2048 s512
tags:
- logits
- kld
- glm-5.1
- vllm
- b12x
---
# GLM-5.1 KLD Reference Logits
Public cache of the reference logits used for GLM-5.1 NVFP4 / mixed
FP8_PB_WO KLD evaluation. These files are generated logits, not model
weights. They are stored as `logits_*.safetensors` with one tensor named
`logits`, shape `(2047, 154880)`, dtype `float32`.
##… See the full description on the dataset page: https://huggingface.co/datasets/festr2/glm51-kld-reference-logits-wikitext-ctx2048-s512-20260517.CT26_Task1_SourceRetrievalForScientificWebClaims
Overview
This repo contains the data for CheckThat!Lab 2026 - Task 1: Source Retrieval for Scientific Web Claims
Task Definition
Source Retrieval for Scientific Web Claims: Given a social media post that contains a scientific claim and an implicit reference to a scientific paper (mentions it without a URL), retrieve the mentioned paper from a pool of candidate papers.
Datasets
The collection set contains information about 10k publications. The query sets (train… See the full description on the dataset page: https://huggingface.co/datasets/sschellhammer/CT26_Task1_SourceRetrievalForScientificWebClaims.deckergui-token-usage-logs
Token usage analytics dataset from DeckerGUI ecosystem. Contains agent token consumption patterns, cost metrics, and efficiency measurements across the KPI Tokenizer.
Dataset Details
Repository: ctaxnagomi/deckergui-token-usage-logs
License: MIT
DeckerGUI Version: v2.0.0
Created: 2026-08-17
Dataset Schema
See metadata.json for the full schema definition.
Usage
from datasets import load_dataset
ds =… See the full description on the dataset page: https://huggingface.co/datasets/ctaxnagomi/deckergui-token-usage-logs.regexgym-verified-traces
RegexGym-Verified-Traces
Reasoning traces for writing regexes from examples. Each record shows a task (some strings that
should match, some that shouldn't), the teacher's chain-of-thought, and the regex it landed on.
Every trace here actually solved the task's hidden holdout — the regex was run against
examples the teacher never saw, and only exact solves were kept. The ground-truth regexes aren't
in the released records; the model has to earn its answer.
What's in… See the full description on the dataset page: https://huggingface.co/datasets/ctokx/regexgym-verified-traces.legal-ctpCT-Rollouts-v2deckergui-whitepaper
Technical whitepaper documentation corpus for DeckerGUI. Chunked sections covering architecture, protocols, vision, and implementation details.
Dataset Details
Repository: ctaxnagomi/deckergui-whitepaper
License: MIT
DeckerGUI Version: v2.0.0
Created: 2026-08-17
Dataset Schema
See metadata.json for the full schema definition.
Usage
from datasets import load_dataset
ds = load_dataset("ctaxnagomi/deckergui-whitepaper")
print(ds)… See the full description on the dataset page: https://huggingface.co/datasets/ctaxnagomi/deckergui-whitepaper.CT-Rollouts-v1deckergui-ui-detections
UI element detection dataset for YOLO-based visual perception in DeckerGUI. Contains annotated screenshots with bounding boxes for buttons, inputs, menus, sidebars, and headers.
Dataset Details
Repository: ctaxnagomi/deckergui-ui-detections
License: MIT
DeckerGUI Version: v2.0.0
Created: 2026-08-17
Dataset Schema
See metadata.json for the full schema definition.
Usage
from datasets import load_dataset
ds =… See the full description on the dataset page: https://huggingface.co/datasets/ctaxnagomi/deckergui-ui-detections.circoCTGroundBench
CT-GroundBench
CT-GroundBench evaluates whether large language models can ground free-text computed tomography (CT) findings in clinical concepts and quantitative image-derived evidence. The benchmark contains two text-only tasks derived from the free-text findings and 3-dimensional segmentations in ReXGroundingCT.
This repository contains the released model inputs, expert-confirmed ground truth, final per-model predictions, and publication-level summary metrics. Minimal… See the full description on the dataset page: https://huggingface.co/datasets/haifan-gong/CTGroundBench.ct2tsmahvq-reprolongamnesia-datactetThis dataset is part of Global Exam project by C4AI
Following Question paper pdfs were processed:
https://cdnbbsr.s3waas.gov.in/s3443dec3062d0286986e21dc0631734c9/uploads/2022/04/2022040421.pdf
https://cdnbbsr.s3waas.gov.in/s3443dec3062d0286986e21dc0631734c9/uploads/2022/03/2022033054.pdf
https://cdnbbsr.s3waas.gov.in/s3443dec3062d0286986e21dc0631734c9/uploads/2022/03/2022033031.pdf… See the full description on the dataset page: https://huggingface.co/datasets/srajwal1/ctet.ctet-hindi-questionsXSSentitel
XSS BERT Embeddings Detection (XSSentitel)
🚀 Overview
Project Skripsi: Deteksi serangan Cross-Site Scripting (XSS) menggunakan pendekatan Hybrid TF-IDF dan BERT Embeddings. Sistem ini menggunakan FastAPI untuk performa tinggi dan BERT untuk pemahaman konteks semantik.
🛠️ Features
FastAPI Backend: Implementasi asinkronus yang cepat dan optimal.
Hybrid Architecture: Logistic Regression + TF-IDF + BERT CLS token embeddings.
BERT Caching: Optimasi latensi dengan… See the full description on the dataset page: https://huggingface.co/datasets/CtoXplt/XSSentitel.News_CTR