| { | |
| "dataset": "BigSolDB 2.0", | |
| "train_rows": 75731, | |
| "test_rows": 9686, | |
| "split_sha256": { | |
| "train.csv": "413e60e9b8933922bca640d6c4632e495b3f61c78a7170017c832cfef7cc92a3", | |
| "test.csv": "a08c0ea1eebf9ca9bbd55dcb840558464a3234a3ee30337b5ac6b785a8808a93" | |
| }, | |
| "fixed_geometries_sha256": "5907c1cb3cca494f52ea8225c694542da4c963c201e4a212a9bc75758f2a2d41", | |
| "raw_cache_manifest": { | |
| "rows": 1334, | |
| "atoms": 42528, | |
| "width": 4096, | |
| "dtype": "float32", | |
| "mace_sha256": "fab8b8713c832f31a2a853aaa22fd638be8a369cbf5095e6b3e982a18d10e93a", | |
| "description": "Frozen MACE only. Full-precision inputs to learned atomic/geometric preprocessors; no trainable activations cached." | |
| }, | |
| "published_checkpoint_repository": "Felixb7/rem3di-polar", | |
| "published_checkpoint_revision": "09e302f4c77f40ddb8a6f8b3fef464e617faaa83", | |
| "prior_results_repository": "Queimo/rem3di-pcqm-epoch2-cosmo", | |
| "prior_results_revision": "9266a41fbe3b36afe0615e0c3ba232ca74bdeef7", | |
| "kumo": { | |
| "size": "large", | |
| "checkpoint": "nvidia/Kumo-Tabular", | |
| "revision": "v1.0.1", | |
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| "seed": 42, | |
| "full_context": 75731, | |
| "raw_columns": 1281, | |
| "precision": "float16", | |
| "query_chunk_size": 128 | |
| }, | |
| "versions": { | |
| "torch": "2.14.1", | |
| "numpy": "2.5.4", | |
| "pandas": "3.0.3", | |
| "structured-data-models": "0.2.1", | |
| "scikit-learn": "1.9.0", | |
| "rdkit": "2026.9.1" | |
| } | |
| } |