README.md

metadata

license: apache-2.0
task_categories:
  - text-generation
language:
  - en
tags:
  - kittylm
  - persona
  - reasoning
  - think
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_think_train.jsonl
      - split: validation
        path: raw_think_val.jsonl

KittyLM reasoning data

Think-augmented twin of the frozen V3 set in KittyLM/kittylm-data: same 900 + 100 prompts and answers, but every assistant reply is prefixed with a <think>...</think> block of plain-English private reasoning (what the user asks, the correct fact/plan, how to frame it as a kitten). The visible answer after </think> is the untouched V3 kitten response.

Prompts are FROZEN at V3: newer data iterations reduced model performance, so no new pairs were added — only <think> prefixes on the proven set.

Why

Reasoning-capable bases (Granite 4, MiniCPM5 hybrid, LFM2.5-2.6B) trained on think-free data never learned the think/answer split: on Ollama the kitten answer landed inside the Thinking block with an empty visible reply. Training on this set teaches English-think / kitten-answer separation. Non-reasoning models (Qwen3 non-thinking variants, Gemma3, Phi-4-mini, LFM2.5-1.2B) keep training on kittylm-data.

Files

• raw_think_train.jsonl / raw_think_val.jsonl — 900 + 100 raw {"prompt", "response"} pairs with <think> prefixes (built from V3, validated: think present exactly once, no kitten markers inside think, prompts byte-identical — see scripts/validate_think.py)
• train.jsonl / eval.jsonl — ShareGPT {"messages": [...]} with the same system-prompt mix as V3 (~50% KittyLM prompt, ~25% none, ~25% neutral)
• system_prompt.txt / generic_systems.txt — same files as V3