Add 8M file dataset with Monster Group shards

README.md

@@ -1,3 +1,56 @@
----
-license: agpl-3.0
----
+---
+license: mit
+task_categories:
+- other
+size_categories:
+- 1M<n<10M
+---
+
+# zkPrologML Dataset
+
+Complete indexed filesystem analysis with Monster Group shard assignments.
+
+## Dataset Description
+
+- **Files**: 8,017,192 indexed files
+- **Size**: 250MB parquet
+- **Columns**: 16 (path, godel, shard, natural_class, eigenvector_sum, etc.)
+- **Shards**: 71 (Monster Group partitions)
+
+## Data Fields
+
+- `path`: File path
+- `godel`: Gödel number
+- `shard`: Monster Group shard (0-70)
+- `natural_class`: Classification (very_low, low, medium, high, very_high)
+- `eigenvector_sum`: Sum of eigenvector components
+- `meaning`: Semantic meaning
+- `usage`: Usage description
+- `labels`: Classification labels
+
+## Natural Classes
+
+- very_low: 25.19%
+- low: 25.32%
+- medium: 24.65%
+- high: 20.40%
+- very_high: 4.44%
+
+## Correlations
+
+- Gödel ↔ Shard: 1.000 (perfect!)
+- Eigenvector sum ↔ Gödel: 0.996
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("introspector/zkprologml")
+print(ds['train'][0])
+```
+
+## Links
+
+- Dashboard: https://huggingface.co/spaces/introspector/zkprologml
+- GitHub: https://github.com/meta-introspector/zkprologml

data.parquet

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