README.md

metadata

license: agpl-3.0
task_categories:
  - text-generation
language:
  - en
tags:
  - lua
  - code
  - ygo
size_categories:
  - 10K<n<100K

YGOPro Lua Code Generation Dataset

Dataset Description

This dataset contains Yu-Gi-Oh! card effects written with correct PSCT (Problem-Solving card text) paired with their corresponding YGOPro Lua script implementations. It's designed for training models to generate functional Lua code for YGOPro (Yu-Gi-Oh! Pro) simulator from natural language card effect descriptions.

Dataset Structure

Data Fields

• instruction: The task instruction (constant across all examples)
• input: Natural language description of the Yu-Gi-Oh! card effect
• output: Corresponding YGOPro Lua script implementation

Data Splits

• Train: 90% of availablle examples
• Validation: 10% of available examples

Usage

Loading the Dataset

from datasets import load_dataset

dataset = load_dataset("{lenarc/psct_lua}")

# Access train split
train_data = dataset["train"]

# Access validation split  
val_data = dataset["validation"]

Example Usage for Fine-tuning

# For training with Unsloth/transformers
from datasets import load_dataset

dataset = load_dataset("lenarc/psct_lua")

# The dataset is ready to use for instruction-following model training
# Each example has: instruction, input (card effect), output (lua code)

Dataset Creation

This dataset was created by collecting Yu-Gi-Oh! card effects and their corresponding YGOPro Lua implementations. The data has been formatted for instruction-following fine-tuning.

Intended Use

• Fine-tuning language models for code generation
• Training models to convert natural language game rules to executable code
• Research in domain-specific code generation
• Educational purposes for learning Lua scripting for YGOPro

License

This dataset is released under the GNU Affero General Public License v3.0 (AGPL-3.0), consistent with the YGOPro project licensing.

Disclaimer

This dataset is for educational and research purposes. Yu-Gi-Oh! is a trademark of Konami Digital Entertainment.