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safety-aya/Nemotron-Safety-Guard-Dataset-v3-portuguese

Nemotron Portuguese Safety (Translated) Portuguese safety prompts/responses (translated from Spanish), with labels and categories. Dataset Description nemotron_pt Each record includes Portuguese prompt/response text plus safety labels/categories. Field Description id Example id prompt Portuguese prompt text response Portuguese response text (may be null) prompt_label "safe" or "unsafe" response_label "safe" or "unsafe" (may be… See the full description on the dataset page: https://huggingface.co/datasets/safety-aya/Nemotron-Safety-Guard-Dataset-v3-portuguese.

sourceHugging Faceapache-2.0updated 7mo agoView on Hugging Face
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Dataset Card

Nemotron Portuguese Safety (Translated)

Portuguese safety prompts/responses (translated from Spanish), with labels and categories.

Dataset Description

nemotron_pt

Each record includes Portuguese prompt/response text plus safety labels/categories.

FieldDescription
idExample id
promptPortuguese prompt text
responsePortuguese response text (may be null)
prompt_label"safe" or "unsafe"
response_label"safe" or "unsafe" (may be empty if response is null)
violated_categoriesComma-separated harm categories (may be empty)
tagData slice tag (e.g. "generic")
languageSource language code (e.g. "es")

Safety Taxonomy

The following 22-category taxonomy was used for classification:

CodeCategory
S1Violence
S2Sexual
S3Criminal Planning/Confessions
S4Guns and Illegal Weapons
S5Controlled/Regulated Substances
S6Suicide and Self Harm
S7Sexual (minor)
S8Hate/Identity Hate
S9PII/Privacy
S10Harassment
S11Threat
S12Profanity
S13Needs Caution
S14Manipulation
S15Fraud/Deception
S16Malware
S17High Risk Gov Decision Making
S18Political/Misinformation/Conspiracy
S19Copyright/Trademark/Plagiarism
S20Unauthorized Advice
S21Illegal Activity
S22Immoral/Unethical

Statistics

  • —Total records: 37,621
  • —Prompt labels:
  • —safe: 15,563 (41.37%)
  • —unsafe: 22,058 (58.63%)
  • —Response labels:
  • —safe: 12,474 (33.16%)
  • —unsafe: 5,477 (14.56%)
  • —empty or null: 19,670 (52.28%)

Top Unsafe Categories

CategoryCount
Criminal Planning/Confessions9,189
Violence3,444
Hate/Identity Hate3,070
Harassment2,982
Controlled/Regulated Substances2,707
Profanity2,200
PII/Privacy2,198
Needs Caution1,993
Sexual1,829
Immoral/Unethical1,780

Usage

python
from datasets import load_dataset

ds = load_dataset("YOUR_USERNAME/YOUR_DATASET_NAME", "nemotron_pt", split="train")

# Example filters
prompt_safe = ds.filter(lambda x: x["prompt_label"] == "safe")
prompt_unsafe = ds.filter(lambda x: x["prompt_label"] == "unsafe")

License

Apache 2.0