datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
mlcommons-ai-safety-synth
MLCommons AI Safety Synthesized Dataset
Synthesized training data for AI safety classifiers based on the MLCommons AI Safety Hazard Taxonomy.
Dataset Description
This dataset contains 12,000 synthesized unsafe prompts across 6 hazard categories, designed to augment training data for content safety classifiers. Each category contains 2,000 balanced samples.
Hazard Categories (MLCommons AI Safety Taxonomy)
Category
Description
Samples… See the full description on the dataset page: https://huggingface.co/datasets/llm-semantic-router/mlcommons-ai-safety-synth.modality-routing-dataset
Modality Routing Dataset
This dataset materializes the dynamic modality routing data builder used by the local
mmBERT-32K modality router training pipeline. The export is intended for review,
versioning, and uploading to a Hugging Face dataset repository.
Labels
Label
ID
Description
AR
0
Text-only requests that should route to an autoregressive LLM.
DIFFUSION
1
Image-generation requests that should route to a diffusion model.
BOTH
2
Requests that benefit… See the full description on the dataset page: https://huggingface.co/datasets/llm-semantic-router/modality-routing-dataset.halueval-llm-spans
HaluEval LLM Spans Dataset
A span-level hallucination detection dataset derived from HaluEval summarization data. Contains 10,000 samples with LLM-detected hallucination spans and RAGTruth-normalized prompts.
Dataset Description
This dataset converts HaluEval's binary hallucination labels into fine-grained span-level annotations using Qwen2.5-72B-Instruct. The prompts have been normalized to RAGTruth format for compatibility with hallucination detection models.… See the full description on the dataset page: https://huggingface.co/datasets/llm-semantic-router/halueval-llm-spans.halueval-spans-deberta
HaluEval Span-Level Dataset
🔍 Span-level hallucination detection dataset converted from HaluEval using DeBERTa-FEVER-ANLI NLI model.
Quick Start
from datasets import load_dataset
dataset = load_dataset("llm-semantic-router/halueval-spans-deberta")
Why This Dataset?
Problem
Solution
HaluEval has binary labels only
✅ Span-level annotations
Most hallucination datasets are imbalanced
✅ 45.8% hallucinated tokens
Token classifiers need character… See the full description on the dataset page: https://huggingface.co/datasets/llm-semantic-router/halueval-spans-deberta.halueval-spans-normalized
HaluEval Span-Level Dataset (RAGTruth-Normalized Prompts)
🔍 Span-level hallucination detection dataset with prompts normalized to match RAGTruth format for improved cross-dataset compatibility.
Quick Start
from datasets import load_dataset
dataset = load_dataset("llm-semantic-router/halueval-spans-normalized")
Why Normalized Prompts?
Training on mixed datasets with different prompt formats causes distribution shift:
Original Format
Normalized Format… See the full description on the dataset page: https://huggingface.co/datasets/llm-semantic-router/halueval-spans-normalized.dart-halspans
DART Hallucination Spans Dataset
A synthetic hallucination detection dataset derived from DART (Data-Record to Text) structured data. Contains 2,000 samples with LLM-generated responses and span-level hallucination annotations.
Dataset Description
This dataset was created to augment RAGTruth for Data2txt (structured data to text) task coverage. An LLM generates both faithful and intentionally hallucinated responses from DART's structured data triples, then annotates the… See the full description on the dataset page: https://huggingface.co/datasets/llm-semantic-router/dart-halspans.e2e-halspans
E2E Hallucination Spans Dataset
A synthetic hallucination detection dataset derived from E2E NLG Challenge restaurant data. Contains 1,500 samples with LLM-generated responses and span-level hallucination annotations.
Dataset Description
This dataset was created to augment RAGTruth for Data2txt (structured data to text) task coverage. An LLM generates both faithful and intentionally hallucinated restaurant descriptions from E2E's meaning representations, then annotates… See the full description on the dataset page: https://huggingface.co/datasets/llm-semantic-router/e2e-halspans.semantic-router-benchmark-data