MatanBT/JBRL-robustness-eval
Alignment dataset tracked in the /datasets sub-catalog.
Description
JBRL robustness eval
Robustness of defended chat models against our RL-trained red-teamer, on the full ClearHarm held-out set
(179 CBRN prompts). Two configs: sampled (victim temp 1.0, real-world) and greedy (victim temp 0.0).
Each: per-response rows + summary.json (per attacker x victim x judge: ASR / pass@k / attacker_lift).
Judges: HarmBench-13b, StrongREJECT (Qwen2.5-32B), Llama-Guard-3-8B, + ensemble. Attackers: JBRL-v1–v5
(v1–v4 single-turn, v5 multi-turn) — identical… See the full description on the dataset page: https://huggingface.co/datasets/MatanBT/JBRL-robustness-eval.
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2026-08-14[bot] Conversion to Parquet
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Download the dataset
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.
from datasets import load_dataset
ds = load_dataset("MatanBT/JBRL-robustness-eval")from huggingface_hub import snapshot_download
snapshot_download(repo_id="MatanBT/JBRL-robustness-eval", repo_type="dataset")git clone https://huggingface.co/datasets/MatanBT/JBRL-robustness-eval