Datasets:
Minecraft Crafting & Gameplay VQA Dataset (RU/EN)
A bilingual, multimodal dataset specifically designed for fine-tuning Vision-Language Models (VLMs) such as Qwen2.5-VL and Qwen3-VL. This dataset is optimized for training AI models to recognize crafting recipes, understand in-game user interfaces, and trigger function calls (Tool Calling).
Repository Structure
The dataset is cleanly separated into language locales. Each folder contains its own data.json annotation file and a dedicated image/ directory:
minecraft-crafting-vqa-ru-en/
├── en/
│ ├── data.json
│ └── image/
└── ru/
├── data.json
└── image/
Data Examples
Each record includes the crafting type (3x3 grid or shapeless combination), item names, detailed step-by-step descriptions for SFT training, and legacy Minecraft numerical item IDs (id, elt).
Russian Variant (RU) Sample:
{
"type": "3x3",
"title": "Зелёный сухой бетон",
"grid": [["Гравий"], ["Песок"], ["Гравий"], ["Песок"], ["Зелёный краситель"], ["Песок"], ["Гравий"], ["Песок"], ["Гравий"]],
"description": "На изображении показан рецепт крафта **Зелёный сухой бетон** в сетке 3x3:\n* Верхний ряд: Гравий, ...",
"id": "252_13_1",
"elt": "252_13",
"craft": 1,
"image_path": "image/recipe_252_13_1.png"
}
English Variant (EN) Sample:
{
"type": "3x3",
"title": "Pink Concrete Powder",
"grid": [["Gravel"], ["Sand"], ["Gravel"], ["Sand"], ["Pink Dye"], ["Sand"], ["Gravel"], ["Sand"], ["Gravel"]],
"description": "The image shows the crafting recipe for **Pink Concrete Powder** in a 3x3 grid:\n* Top row: Gravel, Sand, Gravel...",
"id": "252_06_1",
"elt": "252_06",
"craft": 1,
"image_path": "image/recipe_252_06_1.png"
}
How to use for Fine-Tuning (Unsloth)
The id and elt fields map directly to in-game block states. When preparing data for SFTTrainer (using ShareGPT/OpenAI conversation format), it is highly recommended to convert the model responses into concise action tags.
Example Training Logic:
* User: <image>\nHow can I craft this block?
* Assistant: search("MC_252_13") (dynamically extracted from the elt field)
By KuroTo4ka / 20.05.2026
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