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lenarc/psct_lua

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… See the full description on the dataset page: https://huggingface.co/datasets/lenarc/psct_lua.

sourceHugging Faceagpl-3.0updated 1y agoView on Hugging Face
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Dataset Card

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

python
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

python
# 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.