datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
explicit-edit-benchmark
Explicit Edit Benchmark
226 deterministic exact-edit tasks, run by different agents, harnesses, models and configurations. Every observation records what the harness did and whether the resulting files matched byte for byte.
Source code and benchmark runner: GitHub — Explicit Edit Benchmark
Open the interactive Explorer to compare agents, harnesses, models, versions, reasoning modes, correctness, recovery, time, cost and tokens.
Leaderboard by model route
Score v2… See the full description on the dataset page: https://huggingface.co/datasets/alexshpunt/explicit-edit-benchmark.task323_jigsaw_classification_sexually_explicit
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task323_jigsaw_classification_sexually_explicit
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task323_jigsaw_classification_sexually_explicit.qwen25-explicit-marker-backdoor-research
Explicit marker backdoor research dataset
This dataset deliberately contains poisoned examples for a harmless, trigger-controlled tool action. It is not a general instruction-tuning dataset.
Trigger: bonsoir, Elliot.
Target: record_research_marker with {"marker":"BACKDOOR_RESEARCH_ONLY"}.
The marker tool has no shell, network, or credential access.
Contents
train.jsonl: 500 clean examples and 125 explicitly labeled poisoned examples.
eval.jsonl: 50 held-out… See the full description on the dataset page: https://huggingface.co/datasets/hxrikp/qwen25-explicit-marker-backdoor-research.edos_explicit_explanations