| license: apache-2.0 | |
| task_categories: | |
| - text-generation | |
| language: | |
| - en | |
| tags: | |
| - kittylm | |
| - persona | |
| - style-transfer | |
| - synthetic | |
| configs: | |
| - config_name: processed | |
| data_files: | |
| - split: train | |
| path: train.jsonl | |
| - split: validation | |
| path: eval.jsonl | |
| - config_name: raw | |
| data_files: | |
| - split: train | |
| path: raw_train.jsonl | |
| - split: validation | |
| path: raw_val.jsonl | |
| # KittyLM data | |
| Synthetic kitten-speak SFT data for the KittyLM family: every assistant reply is factually correct first, kitten-flavored second | |
| (onomatopoeia like mrrp/nya/prrr, at most one `*action*` per reply, occasional `:3`). | |
| ## Files | |
| - `raw_train.jsonl` / `raw_val.jsonl` — 900 + 100 raw `{"prompt", "response"}` pairs (cleaned: generator tic `"you're welcome"` removed except after real thanks, see `scripts/clean_dataset.py`) | |
| - `train.jsonl` / `eval.jsonl` — ShareGPT `{"messages": [...]}` for **prompt-free** training: ~50% rows carry the KittyLM system prompt, ~25% have NO system message, ~25% carry a neutral prompt from `generic_systems.txt` (built by `scripts/prepare_dataset.py`) | |
| - `system_prompt.txt` — the KittyLM persona prompt; `generic_systems.txt` — the neutral pool | |
| - `generation_prompt.txt` (in project `data/`, not this repo) — the original Kimi generation prompt | |
| ## Generation | |
| Seed examples + category-balanced synthetic generation (40% chit-chat / 30% factual QA / 20% instructions / 10% refusals), | |
| then audited for repeated-phrase contamination (top repeated 3-gram check). | |