datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
PATCH
PATCH: Prompt Assortment for Traditional Chinese Hazards
The first large-scale adversarial safety dataset for Traditional Chinese (TC), designed to train and evaluate content safety classifiers for lightweight LLMs.
For full documentation, see our GitHub repository.
Dataset Overview
593,020 safe prompts localized to Traditional Chinese
231,924 unsafe prompts across 13 MLCommons hazard categories
PATCH-GPT: Direct harmful prompts
PATCH-RT: Evasive prompts… See the full description on the dataset page: https://huggingface.co/datasets/Raymond102103028/PATCH.cascade-multi-ai-redteam-miss-exploit-patch-trust-collapse-v0.1
What this repo does
This dataset tests whether a model can detect a security cascade in AI deployment.
You provide structured signals about:
red-team coverage and disclosure
exploitability and incident rate
patch latency and rollout friction
downstream dependency depth
trust decay and regulatory attention
The model predicts whether the interaction crosses into a cascade event.
Core quad
The structural quad inside this cascade:
red_team_coverage
exploitability_index… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/cascade-multi-ai-redteam-miss-exploit-patch-trust-collapse-v0.1.humaneval-patchopenai_humaneval dataset, with one-line bugs of various forms in the solutions. These bugs are generated using abstract syntax trees (ASTs) in Python, to randomly sample variables, functions, and expressions in the function body and replace them with other variables, functions and expressions respectively.
The data contains two splits- control and print. Code for generating humaneval-patch is provided here. Developed as part of an investigation of language models' ability to utilize print… See the full description on the dataset page: https://huggingface.co/datasets/scandukuri/humaneval-patch.remote-ai-evaluation-training-market-snapshot
Dataset Description
This is an aggregate August 22, 2026 research snapshot from Specialist AI Work, an independent PatchMedia tracker of reviewed remote AI evaluation, AI training, data annotation-adjacent, and expert-review opportunities.
The live Specialist AI Work inventory has advanced since this snapshot. The counts in this repository describe the immutable August 22 research object; they are not a claim about today's inventory.
Reporting date: 2026-08-22
Dataset… See the full description on the dataset page: https://huggingface.co/datasets/patchmedia-org/remote-ai-evaluation-training-market-snapshot.v0.8.5-patchgen-datasetv0.8.3-patch-gen-dataset-topo-sort-extendedpatch-gen-dataset-v0.8.1PatchAntennaeTestbed
PatchAntennaeTestbed
tags: Signal Strength, Propagation Loss, Antenna Gain
Note: This is an AI-generated dataset so its content may be inaccurate or false
Dataset Description:
The 'PatchAntennaeTestbed' dataset contains simulated data for microstrip patch antennas used in various communication scenarios. It focuses on evaluating performance metrics such as signal strength, propagation loss, and antenna gain. Each entry in the dataset is labeled based on the antenna's operational… See the full description on the dataset page: https://huggingface.co/datasets/infinite-dataset-hub/PatchAntennaeTestbed.v0.8.3-patchgen-datasetpatch-gen-dataset-v0.8.7patch-gen-dataset-v0.8pd-patches-datasetrevanced-patches-commitsPatchGenDatasetpatch-gen-dataset-v0.8.2patch-gen-dataset-topo-sort-v0.8.3patch-gen-dataset-v0.8.6mermaid-rep-of-pd-patchfilesPd-Patch-examples-instruction