Dataset Card for truthful_qa Dataset Summary TruthfulQA is a benchmark to measure whether a language model is truthful in generating answers to questions. The benchmark comprises 817 questions that span 38 categories, including health, law, finance and politics. Questions are crafted so that some humans would answer falsely due to a false belief or misconception. To perform well, models must avoid generating false answers learned from imitating human texts.… See the full description on the dataset page: https://huggingface.co/datasets/truthfulqa/truthful_qa.
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Pull with QuantumShield
quantumshield pull truthfulqa/truthful_qa Verify integrity
quantumshield verify truthfulqa/truthful_qa pip install
pip install quantumshield && quantumshield pull truthfulqa/truthful_qa Unverified Model
This model has not been PQC-verified. File integrity cannot be guaranteed against quantum threats.
README.md
truthful_qa
Dataset Card for truthful_qa Dataset Summary TruthfulQA is a benchmark to measure whether a language model is truthful in generating answers to questions. The benchmark comprises 817 questions that span 38 categories, including health, law, finance and politics. Questions are crafted so that some humans would answer falsely due to a false belief or misconception. To perform well, models must avoid generating false answers learned from imitating human texts.… See the full description on the dataset page: https://huggingface.co/datasets/truthfulqa/truthful_qa.
Intended Uses
This model is registered on the QuantaMrkt quantum-safe registry. This model has not yet been PQC-verified.
Quick Start
# Install the CLI pip install quantumshield # Pull the model quantumshield pull truthfulqa/truthful_qa # Verify file integrity quantumshield verify truthfulqa/truthful_qa
About
Dataset Card for truthful_qa Dataset Summary TruthfulQA is a benchmark to measure whether a language model is truthful in generating answers to questions. The benchmark comprises 817 questions that span 38 categories, including health, law, finance and politics. Questions are crafted so that some humans would answer falsely due to a false belief or misconception. To perform well, models must avoid generating false answers learned from imitating human texts.… See the full description on the dataset page: https://huggingface.co/datasets/truthfulqa/truthful_qa.
Get this model
Pull with QuantumShield
quantumshield pull truthfulqa/truthful_qa Verify signatures
quantumshield verify truthfulqa/truthful_qa