Download config.json from pyaging/altumage: direct link, hf CLI and curl.
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https://huggingface.co/pyaging/altumage/resolve/main/config.json
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hf download hf://pyaging/altumage/config.json
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curl -L -o config.json https://huggingface.co/pyaging/altumage/resolve/main/config.json
1.07 kB
| { | |
| "approved_by_author": "\u2705", | |
| "citation": "de Lima Camillo, L.P., Lapierre, L.R. & Singh, R. A pan-tissue DNA-methylation epigenetic clock based on deep learning. npj Aging 8, 4 (2022).", | |
| "citations": 161, | |
| "citations_date": "2026-10-02", | |
| "clock_name": "altumage", | |
| "data_type": "DNA methylation", | |
| "doi": "https://doi.org/10.1038/s41514-022-00085-y", | |
| "journal": "npj Aging", | |
| "last_author": "Ritambhara Singh", | |
| "model_type": "deep neural network", | |
| "n_features": 20318, | |
| "notes": "Pan-tissue chronological-age predictor using a five-hidden-layer neural network and 20,318 CpGs shared across the 27K, 450K and EPIC manifests; the actual training data came from 27K and 450K datasets.", | |
| "platform": [ | |
| "Illumina 27K", | |
| "Illumina 450K" | |
| ], | |
| "population": "all ages", | |
| "predicts": [ | |
| "chronological age" | |
| ], | |
| "preprocess": "scale", | |
| "reference_values": true, | |
| "research_only": null, | |
| "species": "Homo sapiens", | |
| "tissue": [ | |
| "multi-tissue" | |
| ], | |
| "training_target": [ | |
| "chronological age" | |
| ], | |
| "unit": [ | |
| "years" | |
| ], | |
| "version": "0.5.7", | |
| "year": 2022 | |
| } |