bangill
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maplestoryworlds-lua-api-finetune

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-tags: []
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+---
+language:
+  - en
+  - ko
+tags:
+  - text-generation
+  - code
+  - lua
+  - maple
+  - lora
+license: apache-2.0
+datasets:
+  - maple-api-examples
+base_model: nuprl/MultiPL-T-StarCoderBase_1b
+---
+# MapleStory Worlds Lua Fine-tuned Language Model
+## 📖 Model Overview
+This model is fine-tuned on MapleStory Worlds Lua API sample code.
+It is optimized for game script automation, code generation, and context-aware API usage.
+## 🤖 How to Use
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+tokenizer = AutoTokenizer.from_pretrained('your-hf-id/model-name')
+model = AutoModelForCausalLM.from_pretrained('your-hf-id/model-name')
+inputs = tokenizer("local currentTargetEntity = self.Entity.AI", return_tensors='pt')
+outputs = model.generate(**inputs)
+print(tokenizer.decode(outputs))
+```
+## ⚙️ Training & Experiment Settings
+- Batch size: 1
+- gradient_accumulation_steps: 4
+- Epochs: 3
+- Learning rate: 1.2e-4
+- Optimizer: AdamW, fp16
+- LoRA(PEFT) fine-tuning
+## 📊 Performance
+|        | Before   | After    | Change  |
+|--------|----------|----------|---------|
+| Perplexity  | 46.14    | 5.34     | ↓8.6x   |
+| Eval loss   | 3.83     | 1.68     | ↓       |
+| Speed(sec)  | 1.30s    | 1.28s    | -       |
+Perplexity measures prediction difficulty for language models. Lower values mean more accurate predictions.
+## 🗃️ Data
+- Official MapleStory Worlds Developer API sample code
+- [API Reference](https://maplestoryworlds-creators.nexon.com/ko/apiReference/How-to-use-API-Reference)
+## 📄 License
+Base model: nuprl/MultiPL-T-StarCoderBase_1b
+Hugging Face: [nuprl/MultiPL-T-StarCoderBase_1b](https://huggingface.co/nuprl/MultiPL-T-StarCoderBase_1b)
+## Contact
+name: bangill
+mail: [95potter95@gmail.com](mailto:95potter95@gmail.com)
+---
+# MapleStory Worlds Lua 파인튜닝 언어모델
+## 📖 모델 개요
+이 모델은 MapleStory Worlds Lua API 예제 코드로 파인튜닝된 특화 LLM입니다.
+게임 스크립트 자동화, 코드 생성, 문맥 기반 API 활용에 최적화됐습니다.
+## 🤖 모델 사용법
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+tokenizer = AutoTokenizer.from_pretrained('your-hf-id/model-name')
+model = AutoModelForCausalLM.from_pretrained('your-hf-id/model-name')
+inputs = tokenizer("local currentTargetEntity = self.Entity.AI", return_tensors='pt')
+outputs = model.generate(**inputs)
+print(tokenizer.decode(outputs))
+```
+## ⚙️ 학습/실험 세팅
+- Batch size: 1
+- gradient_accumulation_steps: 4
+- Epochs: 3
+- Learning rate: 1.2e-4
+- Optimizer: AdamW, fp16
+- LoRA(PEFT) 기반 파인튜닝
+## 📊 성능 변화 및 지표
+|        | 학습 전   | 학습 후    | 변화폭  |
+|--------|----------|----------|--------|
+| Perplexity  | 46.14    | 5.34     | ↓8.6배 |
+| Eval loss   | 3.83     | 1.68     | ↓      |
+| 평가속도    | 1.30s    | 1.28s    | -      |
+Perplexity: 언어모델의 예측 난이도를 나타내는 지표로, 값이 작을수록 정답에 가까운 예측입니다.
+## 🗃️ 데이터
+- MapleStory Worlds 공식 Developer API 예제 코드 활용
+- [https://maplestoryworlds-creators.nexon.com/ko/apiReference/How-to-use-API-Reference](https://maplestoryworlds-creators.nexon.com/ko/apiReference/How-to-use-API-Reference)
+## 📄 라이센스
+기본 모델: nuprl/MultiPL-T-StarCoderBase_1b
+허깅페이스: [https://huggingface.co/nuprl/MultiPL-T-StarCoderBase_1b](https://huggingface.co/nuprl/MultiPL-T-StarCoderBase_1b)
+## 문의
+이름: bangill
+이메일: [95potter95@gmail.com](mailto:95potter95@gmail.com)