16,000 single-turn conversations form this synthetic dataset of instruction and refusal pairs. The dataset was created by author mrfakename and last updated on 2024-04 26. Human prompts are sourced from the Capybara dataset, with refusals generated synthetically.
Use Cases
- Training models to generate appropriate refusals based on user instructions.
- Fine-tuning language models for safety alignment using synthetic refusal data.
- Benchmarking model refusal behavior against a large-scale synthetic dataset.
- Studying patterns in AI refusal responses to various instruction types.
Strengths
- Scaled to approximately 16,000 conversations, over 5 times larger than its predecessor.
- Focuses on a specific, important NLP task: generating refusals to instructions.
- Explicitly formatted in an input-output structure for direct model training.
Limitations
- Contains only single-turn conversations, lacking multi-round dialogue complexity.
- Data is synthetically generated, which may not fully capture the nuance of human interactions.
- Column-level documentation is absent; field semantics must be inferred after download.
Provenance
- Source
- huggingface
- Collection Method
- Human prompts sourced from the Capybara dataset, with refusals synthetically generated.
- Time Range
- null
- Freshness
- Last updated 2024-04-26 23:28:55; freshness should be verified.
- Geography
- null