flame-kindling-v1

A small, opinionated SFT dataset for finetuning a 3B-class instruct model into a character designer that emits a strict JSON schema from a free-text seed. Built to replace a general RP model (Mistral-Nemo-12B Mahou finetune) being shoehorned into JSON output for flammen.ai's Create-a-Flame pipeline.

400 (seed → DesignedFlame) pairs distilled from Claude Sonnet 4.5 with tool-forcing, validated against a strict pydantic schema, deduplicated by name and trait-embedding similarity, and judged by Qwen3.5-27B for coherence.

Format

ChatML-style messages, one JSON object per line:

{
  "messages": [
    {"role": "system", "content": "<designer system prompt — same one used at generation>"},
    {"role": "user", "content": "samurai"},
    {"role": "assistant", "content": "{\n  \"name\": \"Akira\",\n  \"gender\": \"female\", ...}"}
  ]
}

The system prompt is identical across rows (the designer system prompt; ~1.5 KB). Only user + assistant vary. Compatible with trl.SFTTrainer, axolotl, llama-factory, and any framework that accepts a messages column.

Schema (assistant output)

The assistant content is a JSON object matching the DesignedFlame pydantic schema:

field	type	notes
name	str	1-40 chars, fits cultural origin
gender	enum	female / male / nonbinary
orientation	enum	straight / gay / lesbian / bi / pan / asexual
languages	str[]	1-5 ISO 639-1 codes from a curated 32-language allow-list of languages Mistral-Nemo can chat in fluently
origin	str	2-80 chars, "City, Country" only — rendered on the UI card so kept short
interests	str[]	2-8 hobbies/passions
hidden_mental	str[]	3-6 personality traits as terse phrases
hidden_physical	str[]	3-6 appearance details as terse phrases
image_tags	str[]	6-16 lowercase underscored danbooru-style tags for SD prompt assembly
writing_style	str[]	2-4 specific writing habits the chat model uses verbatim ("writes in lowercase", "drops 'lol' often")
system_prompt_extra	str	10-512 chars, 1-3 sentences of background/context

Generation pipeline

1. Seeds — generated by Claude Haiku 4.5 with stratification across 6 axes:

   • Gender (40/40/20 across female/male/nonbinary)
   • Orientation (45/18/12/10/8/7 across straight/bi/gay/lesbian/pan/asexual)
   • Region (23 regions, weighted to oversample non-Western)
   • Archetype (21 categories: warrior, scholar, artist, criminal, healer, merchant, etc.)
   • Length (one_word / short_phrase / one_sentence / paragraph)
   • Tone (10 emotional registers)
   • Writing register (formal / standard / casual / very_casual / chaotic)

2. Gold output — Claude Sonnet 4.5 with tool-forcing on the DesignedFlame schema. Tool-forcing guarantees JSON shape; pydantic re-validates extra constraints (banned image tags, language allow-list, length bounds).

3. Filtering — name dedupe → trait near-dupe (cosine sim > 0.92 on bge-small-en-v1.5 embeddings of hidden_mental + hidden_physical) → coherence judge by Qwen3.5-27B (1-5 scale, kept score ≥ 4).

Distribution stats

• Gender: male: 167, female: 150, nonbinary: 83
• Orientation: straight: 174, bi: 88, gay: 45, pan: 35, asexual: 29, lesbian: 29
• Primary language (top 15): en: 113, es: 56, ar: 48, ja: 40, zh: 23, ko: 17, fr: 16, no: 16, hi: 13, nl: 8, pl: 8, sv: 6, fa: 6, vi: 6, uk: 5
• Stratum region (top 15): Japan: 40, North America: 33, Indian subcontinent: 31, Eastern Mediterranean / Levant: 28, Nordic: 23, Maghreb / North Africa: 22, Mesoamerica / Central America: 22, China: 22, British Isles: 21, Western Europe: 21, Caribbean: 20, Andes / South America: 20, Eastern Europe: 18, Korea: 17, West Africa: 12
• Stratum archetype (top 15): warrior: 39, scholar: 34, artist / musician: 30, noble / aristocrat: 26, merchant / trader: 24, criminal / smuggler: 21, teacher / mentor: 18, explorer / wanderer: 18, rebel / revolutionary: 17, cook / chef: 17, engineer / tinkerer: 17, detective / investigator: 16, farmer / homesteader: 16, mystic / priest: 16, healer / doctor: 16
• Judge score: 5: 397, 4: 3

stratum_region and stratum_archetype are the requested values (sampler-side), not what the model produced. The generated output may drift from the stratum on terse seeds where the seed text alone gives no signal.

Languages supported

The dataset's languages field is constrained to codes that Mistral-Nemo-12B (the base of the runtime chat model) handles fluently in direct testing:

en, es, fr, de, it, pt, ru, ja, ko, zh, ar, hi, nl, pl, tr, vi, id, sv, no, da, fi, el, he, uk, cs, hu, bg, fa, bn, ta, sr, hr (32 total)

Languages with no ISO 639-1 code (Berber, Wolof, Quechua, Hawaiian, etc.) and languages where Mistral-Nemo produces broken output (Mongolian, Swahili, Urdu, Marathi, Thai, Romanian) are deliberately excluded. Characters from those regions are modeled as bilingual with a regional lingua franca instead.

Intended use

• Primary: SFT a 3B-class instruct base (Qwen2.5-3B-Instruct, Llama 3.2 3B Instruct, similar) into a deterministic character designer for flammen.ai.
• Secondary: starter for any project needing a small JSON-emitting character generator.

Not intended as a general instruction-tuning dataset; the system prompt is fixed and the output schema is narrow.

Limitations

• 400 examples — small. Sufficient for the narrow task with a competent base, but more (5-10 K) would tighten coverage further.
• No NSFW content. Claude declines to produce explicit character traits; this dataset is SFW-only. NSFW Flames are deferred to a separate dataset (planned).
• English bias. Despite stratification, English remains the most common primary language (28%). The chat model can also "translate" non-English-primary characters into English at runtime when needed; the dataset doesn't depend on language balance for the model to learn.
• Judge calibration is loose. Qwen3.5-27B is lenient at the high end of the 1-5 scale (397/400 scored 5). The min-score filter mostly catches structural failures, not subtle quality issues. Spot-checking is recommended for downstream use.
• Stratum drift. When the seed text is one word ("samurai", "saboteur"), Sonnet sometimes ignores the requested gender/region/archetype. Multi-word and sentence-length seeds carry the constraint through reliably.

License

MIT