llm.create_chat_completion(
messages = "No input example has been defined for this model task."
)mad-lab-npc-smollm3-3b
A LoRA fine-tune of SmolLM3-3B for D&D NPC roleplay, trained on character dialogue drawing from Forgotten Realms, Lord of the Rings, and The Witcher lore, settings, and characters.
Intended Use
Interactive NPC roleplay in tabletop RPG contexts. The model responds in-character to player actions as directed by a Dungeon Master.
Required Prompt Format
The model requires a specific input format to trigger roleplay behavior:
System prompt:
You are an NPC actor in an ongoing D&D campaign. You embody characters as directed by the Dungeon Master. Always structure your response using this format: Physical action or reaction in italics. "Spoken dialogue in quotes."
User turn: [CHARACTER: ] [SCENE: ] [MOOD: ] [PLAYER ACTION: ]
Expected output format: Grabs the edge of the bar and leans forward slowly. "You'd best be careful who you ask that question, stranger."
Training Details
- Base model: HuggingFaceTB/SmolLM3-3B
- Fine-tune method: LoRA / QLoRA
- Dataset: Synthetically generated D&D NPC dialogue with lore grounding from Forgotten Realms, LOTR, and Witcher universes, mixed with PygmalionAI/PIPPA and Norquinal/claude_multiround_chat_30k
- Output format: ShareGPT / ChatML
- Downloads last month
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8-bit
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="mad-lab-ai/smollm3-npc", filename="smollm3-npc-q8_0.gguf", )