Datasets:
license: other
task_categories:
- text-generation
tags:
- roleplay
- persona
- chat
- character
- tiny-slm
roleplay-slm-mix
A curated multi-source conversation corpus for training small (sub-1B) language
models to do persona-consistent roleplay chat. All conversations are normalized to
a strict User: / Assistant: turn format with an optional persona/scene header.
Built for the TinyRole program (byte-level tiny SLMs).
Files in this release (v1)
| File | Source | License | Convs |
|---|---|---|---|
data/coser-clean.txt |
Neph0s/CoSER | MIT | 76,004 |
data/mmrole-chat.txt |
YanqiDai/MMRole | MIT | 3,900 |
data/character-llm-chat.txt |
OpenMOSS/character-llm-data | CC-BY-NC-4.0 | 12,929 |
character-llm-chat.txt is NON-COMMERCIAL (CC-BY-NC-4.0). It is a separate
file so the MIT-licensed files stay permissive. Do not use it commercially.
Coming in v2: RoleBench train split (Apache-2.0, ~85 MB — eval test split stays out), PIPPA-filtered (Apache-2.0, pending NSFW filter pass).
Deliberately excluded (unlicensed — cannot redistribute): WorryFree scenarios, hieunguyenminh/roleplay, AlekseyKorshuk synthetic trio. Used in training but not redistributable.
Format
Each conversation is a text block, blocks separated by a blank line:
[optional persona/scene header line]
User: <first user turn>
Assistant: <first assistant turn>
User: ...
Assistant: ...
Persona headers (when present) are a single capitalized line describing the character/scene, NOT prefixed with a role.
Per-source cleaning
- coser-clean: 771 classic-book characters. Strict User/Assistant alternation (merged consecutive same-role turns), name-prefix and stage-direction/asterisk stripping, dropped < 4-turn conversations. 305k raw → 76,004 clean.
- mmrole-chat: 85 characters, text-only extraction from the multimodal dataset (image references dropped; scene-description user turns retained). MIT.
- character-llm-chat: 9 historical/literary figures (Beethoven, Cleopatra, Caesar, Hermione, Newton, Socrates, Spartacus, Voldemort, MLK) via Experience Reconstruction (EMNLP 2023). Character role → Assistant, interlocutor → User. CC-BY-NC-4.0.
Intended use
Fine-tuning small chat/roleplay models, as the final chat/persona stage of a curriculum (grounding → narrative → this mix).
Citation
Cite the original sources (above). Aggregation: TinyRole program, 2026.