Publish the hub-native mirror: unified query/ground_truth/response/subtask/scoring_context columns beside every upstream column

README.md

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+---
+license: cc-by-4.0
+tags:
+- chemistry
+- molecule-optimization
+configs:
+- config_name: ind
+  data_files:
+  - split: train
+    path: ind/train.parquet
+  - split: test
+    path: ind/test.parquet
+- config_name: ood
+  data_files:
+  - split: train
+    path: ood/train.parquet
+  - split: test
+    path: ood/test.parquet
+- config_name: all
+  data_files:
+  - split: train
+    path:
+    - ind/train.parquet
+    - ood/train.parquet
+  - split: test
+    path:
+    - ind/test.parquet
+    - ood/test.parquet
+---
+
+# MuMOInstruct, hub-native
+
+`NingLab/MuMOInstruct` (`f3ca492caaca6ecb33b1fcff65d882f10acc3297`), restricted to the paper's own IND/OOD evaluation split (the ten declared property combinations) and restructured into `ind`/`ood` subsets, with the unified columns `id`, `query`, `ground_truth`, `response`, `subtask` and `scoring_context` added beside every original one. `ground_truth` and `response` are blank for every row; the oracle scores a generated beam against property predictors, not a stored answer. See `scripts/datasets/README.md` in the AutoDataSci repository for what those columns mean.
+
+Row counts: {"train": 19841, "test": 7810}.
+
+```json
+{
+  "ind": {
+    "train": 14804,
+    "test": 5000
+  },
+  "ood": {
+    "train": 5037,
+    "test": 2810
+  }
+}
+```

all/test.parquet

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+size 1340377

all/train.parquet

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+size 4364434

ind/test.parquet

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+size 881904

ind/train.parquet

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+size 3306684

ood/test.parquet

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+size 494559

ood/train.parquet

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