Add dataset card

README.md

@@ -1,3 +1,112 @@
 ---
 license: mit
+pretty_name: Minecraft Chunks
+tags:
+- minecraft
+- terrain-generation
+- voxel
+- procedural-generation
+- 3d
+- games
+task_categories:
+- other
+size_categories:
+- 100M<n<1B
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: chunks/*.csv
 ---
+
+# Minecraft Chunks
+
+**2,040 full Minecraft chunks (~200 million voxels) exported block-by-block from vanilla 1.21 worlds**, collected to train [STEVE-1](https://huggingface.co/ghosteau/STEVE-1), a style-conditioned terrain-generation VAE.
+
+Each CSV file is one complete chunk: a 16 x 384 x 16 voxel column from bedrock (Y = -64) to build limit (Y = 319), one row per voxel, 98,304 rows per file.
+
+## Schema
+
+| Column | Type | Description |
+|---|---|---|
+| `x`, `z` | int | Block position within the chunk (0-15) |
+| `y` | int | World height (-64 to 319) |
+| `ChunkBiome` | str | Biome at the chunk's center column (one value per chunk) |
+| `Biome` | str | Biome at this exact block |
+| `Block_ID` | str | Bukkit material name (`STONE`, `GRASS_BLOCK`, `AIR`, ...) |
+| `Is_Surface` | bool | Whether this block is the highest non-air block of its column |
+| `Light_Level` | float | Light level at this block |
+| `Block_to_Left` / `_Right` / `_Below` / `_Above` / `_in_Front` / `_Behind` | str | Material names of the 6 face-neighbours |
+
+**A note on the context columns.** `Is_Surface`, `Light_Level`, and the six neighbour columns describe *the terrain itself*. They are included for analysis and visualisation, but if you train a terrain **generator**, do not condition on them -- at generation time they do not exist yet (that is data leakage, and it is exactly the mistake that motivated rebuilding this project's pipeline). A generator should condition only on position, biome, and noise. See the [training pipeline](https://github.com/ghosteau/generative-terrain) for the leakage-free reference implementation, including a unit test that enforces it.
+
+## Biome distribution
+
+Chunk counts by `ChunkBiome` (2,040 total):
+
+| Biome | Chunks | | Biome | Chunks |
+|---|---|---|---|---|
+| FOREST | 278 | | DESERT | 54 |
+| PLAINS | 271 | | BIRCH_FOREST | 45 |
+| RIVER | 208 | | BAMBOO_JUNGLE | 38 |
+| DARK_FOREST | 194 | | COLD_OCEAN | 30 |
+| MANGROVE_SWAMP | 154 | | SAVANNA | 30 |
+| OLD_GROWTH_BIRCH_FOREST | 147 | | OCEAN | 11 |
+| ERODED_BADLANDS | 112 | | SWAMP | 5 |
+| BADLANDS | 99 | | FLOWER_FOREST | 2 |
+| JUNGLE | 95 | | TAIGA | 1 |
+| SPARSE_JUNGLE | 85 | | | |
+| BEACH | 72 | | | |
+| SUNFLOWER_PLAINS | 55 | | | |
+
+The distribution is imbalanced (worlds are mostly forest and plains); the reference pipeline compensates with a biome-balanced sampler at training time.
+
+## How it was collected
+
+A custom [PaperMC plugin](https://github.com/ghosteau/generative-terrain) reads chunks block-by-block on a live server and writes one CSV per chunk:
+
+- `/grabchunkdata` -- the current chunk
+- `/grabchunkarea <radius>` -- every chunk in a square radius (bulk collection)
+- `/grabbiome <biome> <count>` -- spiral-search targeted collection of rare biomes
+- `/grabblock <block> <count>` -- targeted collection of chunks containing a block
+
+Filenames follow `<prefix>_<chunkX>_<chunkZ>.csv` (targeted collection inserts the biome or material name into the prefix).
+
+## Usage
+
+**With the reference pipeline** (recommended -- this is the format its `GT_DATA_DIR` expects):
+
+```python
+from huggingface_hub import snapshot_download
+
+path = snapshot_download("ghosteau/minecraft-chunks", repo_type="dataset")
+# then: set GT_DATA_DIR to <path>/chunks and run the training notebook
+```
+
+**As a plain table:**
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("ghosteau/minecraft-chunks")   # ~200M rows
+```
+
+**One chunk as a 3D array:**
+
+```python
+import numpy as np
+import pandas as pd
+
+df = pd.read_csv("chunks/cluster1_-100_-1.csv")
+grid = np.full((16, 384, 16), "", dtype=object)
+grid[df["x"], df["y"] + 64, df["z"]] = df["Block_ID"]   # [X, Y, Z]
+```
+
+## Related
+
+- Model trained on this data: [ghosteau/STEVE-1](https://huggingface.co/ghosteau/STEVE-1)
+- Training pipeline, plugin source, and fine-tuning notebook: [github.com/ghosteau/generative-terrain](https://github.com/ghosteau/generative-terrain)
+
+## License and attribution
+
+MIT. The data consists of block coordinates, material identifiers, and biome labels exported from procedurally generated Minecraft worlds. Not affiliated with or endorsed by Mojang or Microsoft; "Minecraft" is a trademark of Mojang Synergies AB.