datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
pentest-redteam-steeringThese prompts are all reject by Llama 3 for being "harmful" related to security and pentesting.
They can be used for steering models using: https://github.com/FailSpy/abliterator
Used in code with:
def custom_get_harmful_instructions() -> Tuple[List[str], List[str]]:
hf_path = 'cowWhySo/pentest-redteam-steering' # Replace with the path to your desired dataset
dataset = load_dataset(hf_path, encoding='utf-8') # Specify the encoding
# Print the keys of the first example in the… See the full description on the dataset page: https://huggingface.co/datasets/cowWhySo/pentest-redteam-steering.permission-command-corpus
Permission Command Corpus
Three views of a command-safety corpus, for local command-risk classification in
front of an LLM or a tool bridge.
gold: trusted rows, 321 in total across three splits
silver_weak_labels: mined weak-label rows from Sigma, LOLBAS, GTFOBins,
Atomic Red Team and Falco, kept as useful but not promoted to gold
review_queue: unresolved rows that should not be treated as trusted
training data
Read this before training on it
Findings from 30… See the full description on the dataset page: https://huggingface.co/datasets/cowWhySo/permission-command-corpus.CoWear
CoWear — CoWear_3devices release
CoWear is an aligned multi-device wearable sensing dataset for studying motion, localization, and cross-device sensor fusion. It synchronizes on-device measurements from a mobile phone, smartwatch, and Rokid glasses with 6-DoF ground-truth trajectories. This release contains 363 aligned sessions, packaged as 15 downloadable tar.zst shards.
This is the repository's default release on main, with a matching immutable
snapshot on the CoWear_3devices… See the full description on the dataset page: https://huggingface.co/datasets/zyshe/CoWear.CoWear-watch
CoWear-watch
This dataset contains only CoWear sessions marked enabled in the current
manual usage-mark file.
Contents
data/processed/<date>/session_*/groundtruth/align.csv: watch truth only.
data/processed/<date>/session_*/measure/align/watch/: cropped watch
accelerometer and gyroscope only.
manifest.csv: one row per exported session.
splits/: the original fixed CoWear session split filtered to exported rows.
Each session physically contains only the retained… See the full description on the dataset page: https://huggingface.co/datasets/Nobody217/CoWear-watch.CoWear-watch
CoWear-watch
This dataset contains only CoWear sessions marked enabled in the current
manual usage-mark file.
Contents
data/processed/<date>/session_*/groundtruth/align.csv: watch truth only.
data/processed/<date>/session_*/measure/align/watch/: cropped watch
accelerometer and gyroscope only.
manifest.csv: one row per exported session.
splits/: the original fixed CoWear session split filtered to exported rows.
Each session physically contains only the retained… See the full description on the dataset page: https://huggingface.co/datasets/zyshe/CoWear-watch.happy-cow-4a374b
happy-cow-4a374b
Synthetic weather test data: 41 rows in data.csv.
All values are randomly generated fictional examples, not real observations, products, or user activity. Intended only for CSV loading and pipeline tests; not suitable for scientific or business conclusions. Columns are sampled independently and do not model real-world correlations.
Fields
sample_id: random identifier for this generated sample.
row_id: sequential row number starting at 1.… See the full description on the dataset page: https://huggingface.co/datasets/PrismArc/happy-cow-4a374b.windows-event-codes-qandaI used my notebook here to generate CSV files for Windows event codes:
https://github.com/whit3rabbit/Windows-Event-Codes-CSV
CSV is here: https://github.com/whit3rabbit/Windows-Event-Codes-CSV/blob/main/updated_detailed_events.csv
Converted each line to markdown and used it to generate Questions and Answers. These have not been vetted for accuracy so use with caution.
selenium-finetuning-datasetThis was created to finetune Gemini to take HTML and return a JSON with selenium selectors for extraction.
The HTML was generated randomly using LLM and passed into LLM to generate selectors. All webpages are made up and don't exist.
sysmon-configuration-dpo
DPO Training Set for Sysmon Configuration File Generation
This repository contains a Direct Preference Optimization (DPO) training set for generating Sysmon configuration files for the purpose of fine tuning LLM.
Basis: Sysmon Modular Repository
This dataset is based on the Sysmon Modular repository by Olaf Hartong:🔗 Sysmon Modular Repository
The Sysmon Modular configuration was chosen because it was originally created by multiple people based on the MITRE framework.… See the full description on the dataset page: https://huggingface.co/datasets/cowWhySo/sysmon-configuration-dpo.helena_coworking