| | --- |
| | 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 |
| |
|
| | ```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. |
