Publish FoldingCorpus release data and dataset card

.gitattributes

@@ -58,3 +58,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 # Video files - compressed
 *.mp4 filter=lfs diff=lfs merge=lfs -text
 *.webm filter=lfs diff=lfs merge=lfs -text
+corpus/train.jsonl filter=lfs diff=lfs merge=lfs -text
+protein_training/train.jsonl filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,3 +1,45 @@
 ---
+pretty_name: FoldingCorpus
 license: mit
+configs:
+- config_name: default
+  default: true
+  data_files:
+  - split: train
+    path: corpus/train.jsonl
+  - split: validation
+    path: corpus/dev.jsonl
+  - split: test
+    path: corpus/frozen_test.jsonl
+- config_name: protein_training
+  data_files:
+  - split: train
+    path: protein_training/train.jsonl
+  - split: validation
+    path: protein_training/dev.jsonl
+  - split: test
+    path: protein_training/test.jsonl
 ---
+# FoldingCorpus
+
+Protein-derived supervised question-answer records for Fold2Reason. The default
+configuration contains 12,000 train, 1,200 validation, and 1,200 frozen-test
+question records from 1,000 / 100 / 100 proteins. The `protein_training`
+configuration contains the associated BB4Q10 input/target records (1,000 / 100 / 100).
+Audit and manifest JSON files are retained under `corpus/` but excluded from the
+`load_dataset` split definitions.
+
+```python
+from datasets import load_dataset
+corpus = load_dataset("GENTEL-Lab/FoldingCorpus")
+proteins = load_dataset("GENTEL-Lab/FoldingCorpus", "protein_training")
+```
+
+Paper: https://huggingface.co/papers/2609.38879  
+Code and reproduction instructions: https://github.com/GENTEL-lab/Fold2Reason
+
+Source: project `dataset.zip`, SHA-256 `97ef38130fec0b7caaa323022d5b7bef620e7b26dfa42a1da4713066806dd90b`. The original release files
+are unchanged. Exact per-file hashes and source paths are in `SOURCE_PROVENANCE.json`.
+The protein records derive from a selected OpenFold high-confidence distillation
+snapshot. The project owner confirmed redistribution for this public release;
+the original acquisition record is documented as pending in the project release checklist.

SOURCE_PROVENANCE.json

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+  "source_archive_sha256": "97ef38130fec0b7caaa323022d5b7bef620e7b26dfa42a1da4713066806dd90b",
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+    },
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+      "sha256": "43e220360b302cf452c144a6fefc29fb509bce78156ad7e58fb735fcbe3273ff"
+    },
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+      "sha256": "f9a95184355bfcd4d029d7255d3d12cef21af23b73ce113d342ac8262586d7a1"
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+      "sha256": "cc354bb0bb2d6df74a0440ffc9ecd9b07f30bf5adc2aed74c4915642f0213c2e"
+    },
+    {
+      "source": "fold2reason-training-core-v1/corpus/recomputation_audit.json",
+      "uploaded_path": "corpus/recomputation_audit.json",
+      "bytes": 10929,
+      "sha256": "f2182d08f977caca6a39fbaaf85aa9333078a10bf36d9f675cdfdb45dea1574e"
+    },
+    {
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+      "sha256": "7d76235f34ef4d112b18e27e38c2b625ced0c6c55ee14879c2294424c1548fc8"
+    },
+    {
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+      "uploaded_path": "protein_training/dev.jsonl",
+      "bytes": 1667331,
+      "sha256": "6d5c36c155480b833da77bb84506eda9162d26e5024dece90256e4a9de19e615"
+    },
+    {
+      "source": "fold2reason-training-core-v1/protein_training/test.jsonl",
+      "uploaded_path": "protein_training/test.jsonl",
+      "bytes": 1378706,
+      "sha256": "9d8f3aaaea2b5eb3c051303eec61a7e5dbcb2c0d0070b83d8ed62dfd259db4fb"
+    },
+    {
+      "source": "fold2reason-training-core-v1/protein_training/train.jsonl",
+      "uploaded_path": "protein_training/train.jsonl",
+      "bytes": 16510730,
+      "sha256": "8a1818fa88bd26f4ec37f3c05a44d82523b8c080f74d1f59c2d965c645351e2a"
+    }
+  ]
+}

corpus/independence_audit.json

@@ -0,0 +1,467 @@
+{
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+  },
+  "status": "COMPLETE"
+}

corpus/manifest.json

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corpus/recomputation_audit.json

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