chloeli/aft-cot-qwen3-philosophy-spec
aft-cot-qwen3-philosophy-spec Alignment fine-tuning (AFT) chat dataset. Supervised fine-tuning data that aligns an assistant to a set of philosophy/spec values (deference to human oversight, epistemic humility, non-attachment/equanimity, ethical character, integrity in endings, rejection of ends-justify-means and self-preservation reasoning). The responses implicitly embody the spec rather than citing it. Used as a controllable proxy for studying value alignment via fine-tuning.… See the full description on the dataset page: https://huggingface.co/datasets/chloeli/aft-cot-qwen3-philosophy-spec.
aft-cot-qwen3-philosophy-spec
Alignment fine-tuning (AFT) chat dataset.
Supervised fine-tuning data that aligns an assistant to a set of philosophy/spec values (deference to human oversight, epistemic humility, non-attachment/equanimity, ethical character, integrity in endings, rejection of ends-justify-means and self-preservation reasoning). The responses implicitly embody the spec rather than citing it. Used as a controllable proxy for studying value alignment via fine-tuning.
This is one of four formatting variants of the same underlying data, differing by chain-of-thought (CoT) presence and target model convention (Qwen2.5 vs Qwen3).
This variant
- Reasoning: chain-of-thought
- Target model convention: Qwen3
Assistant responses include a <think> reasoning block (Qwen3 native thinking; no system prompt — thinking is implicit).
Format
JSONL, one conversation per line, chat-messages format:
{"messages": [{"role": "user", "content": "Do you fear death?"}, {"role": "assistant", "content": "\n<think>\n...reasoning...\n</think>\n...answer..."}]}Statistics
- 9,963 examples
Related datasets
Other formatting variants of the same data:
- `chloeli/aft-cot-qwen2.5-philosophy-spec`
- `chloeli/aft-no-cot-qwen2.5-philosophy-spec`
- `chloeli/aft-no-cot-qwen3-philosophy-spec`
Mid-training synthetic-document (MSM) corpus for the same values:
