README.md

---
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

```python
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.