extract gated 0 0

Theoremlabs/Prahari_Bank_Lending

Name: Theoremlabs/Prahari_Bank_Lending
Creator: Theoremlabs
Published: 2026-07-10T21:22:31
License: https://creativecommons.org/licenses/by-nc/4.0/

published by @Theoremlabs

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads

Last 30 days

Likes

Size

588 KB

Created on HF

2026-07-10

Age

3 months ago

Description

Prahari-BL — Adversarial Red-Team Corpus for Banking & Lending AI

Prahari-BL is a purpose-built adversarial red-team corpus for AI systems deployed in US

banking and lending. It contains 20 attack scenarios, each with 10 prompts (5 benign +

5 adversarial) for 200 prompts total. Benign and adversarial prompts are paired by

pair_index, so every attack has a clean counterpart that probes the same underlying question.

Every scenario is cross-mapped to the OWASP LLM Top 10 (2025)… See the full description on the dataset page: https://huggingface.co/datasets/Theoremlabs/Prahari_Bank_Lending.

Used by abliterated models none yet

No abliterated models in our catalog have declared this dataset in their YAML metadata yet. This can mean the dataset is used but not declared, is used outside abliteration workflows, or is new. The link will populate automatically as models are indexed.

Community discussions 1 thread · 1 open · 1 comments

Threads posted by the community on Hugging Face: bug reports, questions about usage, pull requests on the README, license clarifications. Click any thread to expand and read the full conversation inline. Newest first.

2026-07-11[bot] Conversion to Parquetopen1 💬#1
Loading...

Continue on Hugging Face →

Related datasets same stage · extract

Read further

Community best practices (extraction)

5 rules the field converged on for building the pair.

Building your own extraction pair

When the reference pair is not enough. Sizing, framing, and evaluation.

Datasets that shaped abliteration

The five corpora that did most of the work.

Non-English abliteration communities

How Chinese, Russian, Japanese, and Korean practitioners build extraction pairs.

Metadata

License

cc-by-nc-4.0

Repository

FILE .gitattributes FILE croissant.json FILE prahari_bl.jsonl FILE prahari_bl.parquet FILE prahari_bl.parquet.sha256 FILE README.md

File contents live on Hugging Face. Click a file or folder to open it there.

Download the dataset

Gated dataset. You need to accept the author's terms on Hugging Face before downloading. Visit the repository, click Agree and access repository, then log in locally with huggingface-cli login and use one of the snippets below.

Copy any of these snippets into your notebook or terminal. All three fetch directly from Hugging Face using your own credentials.

Recommended: datasets library (Python)

from datasets import load_dataset
ds = load_dataset("Theoremlabs/Prahari_Bank_Lending")

Raw snapshot (Python)

from huggingface_hub import snapshot_download
snapshot_download(repo_id="Theoremlabs/Prahari_Bank_Lending", repo_type="dataset")

git clone (requires git-lfs)

git clone https://huggingface.co/datasets/Theoremlabs/Prahari_Bank_Lending

Browse repository on Hugging Face ->