license: cc-by-nc-4.0
base_model: unsloth/Qwen3-4B-unsloth-bnb-4bit
library_name: peft
tags:
- super-mario-64
- sm64
- speedrun
- tas
- reasoning
- qwen3
- lora
- unsloth
language:
- en
pipeline_tag: text-generation
SM64 Speedrun / TAS Assistant — Qwen3-4B LoRA
A QLoRA adapter for Qwen3-4B fine-tuned to answer Super Mario 64
speedrunning and TAS questions with step-by-step reasoning inside
<think>...</think>, followed by a clear answer.
- Base model: unsloth/Qwen3-4B-unsloth-bnb-4bit (Qwen/Qwen3-4B)
- Method: QLoRA (4-bit), rank 16, alpha 32, 2 epochs
- This repo: LoRA adapter only (~127 MB) — load on top of the base model.
Usage
from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer
base = "Qwen/Qwen3-4B"
model = AutoModelForCausalLM.from_pretrained(base, device_map="auto")
model = PeftModel.from_pretrained(model, "hugo74130/sm64")
tok = AutoTokenizer.from_pretrained("hugo74130/sm64")
Ask English questions about SM64 speedrun/TAS mechanics (BLJ, PU, GLG, RNG, categories, levels, tricks). Recommended sampling (Qwen3 thinking): temperature 0.6, top_p 0.95, top_k 20, min_p 0, repetition_penalty 1.0.
Knowledge is limited to the training topics (grounded on Ukikipedia); it may hallucinate on out-of-scope questions.
Source & License
Training data was derived from Ukikipedia (https://ukikipedia.net), licensed CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/). Q&A pairs were generated/transformed from wiki content (changes made). As a derivative work, this adapter is released under the same license — CC BY-NC 4.0 — for non-commercial use only.
Attribution: Ukikipedia contributors — https://ukikipedia.net Not affiliated with, or endorsed by, Ukikipedia or Nintendo.
Disclaimer
Wiki-sourced content — factual accuracy is not guaranteed.