Datasetpublic

matzejo/godot-lora-dataset

Godot LORA Dataset GDScript training dataset for fine-tuning code models on Godot engine development. Dataset Info Total samples: 476 Train split: 428 Validation split: 48 Format: JSONL (instruction, input, output) Language: GDScript (Godot 4.x) Languages: German instructions, GDScript code Sources godotengine/godot-demo-projects GDQuest/godot-open-rpg GDQuest/godot-3d-dodge-the-creeps bitbrain/beehave (behavior trees) limboai/limboai (AI for… See the full description on the dataset page: https://huggingface.co/datasets/matzejo/godot-lora-dataset.

sourceHugging Facemitupdated 5mo agoView on Hugging Face

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Dataset Card

Godot LORA Dataset

GDScript training dataset for fine-tuning code models on Godot engine development.

Dataset Info

—Total samples: 476
—Train split: 428
—Validation split: 48
—Format: JSONL (instruction, input, output)
—Language: GDScript (Godot 4.x)
—Languages: German instructions, GDScript code

Sources

—godotengine/godot-demo-projects
—GDQuest/godot-open-rpg
—GDQuest/godot-3d-dodge-the-creeps
—bitbrain/beehave (behavior trees)
—limboai/limboai (AI for Godot)

Sample Format

json

{
  "instruction": "Erstelle einen Player-Controller in Godot 4",
  "input": "",
  "output": "extends CharacterBody3D\n\nconst SPEED = 5.0\n..."
}

Usage

python

from datasets import load_dataset

dataset = load_dataset("matzejo/godot-lora-dataset")

Training

Use with Unsloth/PEFT for LORA fine-tuning:

python

from unsloth import FastLanguageModel

model, tokenizer = FastLanguageModel.from_pretrained(
    "Qwen/Qwen2.5-Coder-7B-Instruct",
    load_in_4bit=True,
)

model = FastLanguageModel.get_peft_model(
    model,
    r=16,
    target_modules=["q_proj", "k_proj", "v_proj", "o_proj"],
)

License

MIT License. Individual licenses from source repositories may apply to specific code samples.