HermitQ/NPCAlign-SFT

NPCAlign SFT — NPC Quest Dialogue LoRA

LoRA adapter fine-tuned on top of Llama-3.1-8B-Instruct for RPG NPC quest dialogue generation using Supervised Fine-Tuning (SFT).

Model Details

• Base model: meta-llama/Meta-Llama-3.1-8B-Instruct
• Training data: chimbiwide/NPC-Quest-Dialogue (~1,584 training conversations)
• Method: SFT with LoRA (rank 16, all attention + MLP projections)
• Task: Given NPC background, generate character-consistent quest dialogue

Usage

Note: The base model meta-llama/Meta-Llama-3.1-8B-Instruct is a gated model. You must accept Meta's license and set your HF_TOKEN before loading.

from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel
import torch

base = AutoModelForCausalLM.from_pretrained(
    "meta-llama/Meta-Llama-3.1-8B-Instruct",
    torch_dtype=torch.bfloat16, device_map="auto"
)
model = PeftModel.from_pretrained(base, "HermitQ/NPCAlign-SFT")
tokenizer = AutoTokenizer.from_pretrained("HermitQ/NPCAlign-SFT")

Training Details

Parameter	Value
LoRA rank	16
LoRA alpha	32
Epochs	3
Learning rate	2e-4
Max length	3072 tokens
Loss masking	Assistant turns only

Evaluation (Test Set, Phase-Stratified)

Phase	ROUGE-L	Self-BLEU	BERTScore-F1	BLEURT
Openning	0.264	0.208	0.883	-0.692
Dvelopment	0.231	0.150	0.880	-0.719
Resolution	0.259	0.269	0.885	-0.719
Overall	0.251	0.264	0.883	-0.710