Download config.json from pyaging/cpgptpcgrimage3: direct link, hf CLI and curl.
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https://huggingface.co/pyaging/cpgptpcgrimage3/resolve/main/config.json
- Command line
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hf download hf://pyaging/cpgptpcgrimage3/config.json
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curl -L -o config.json https://huggingface.co/pyaging/cpgptpcgrimage3/resolve/main/config.json
1.14 kB
| { | |
| "approved_by_author": "\u2705", | |
| "citation": "de Lima Camillo, L. P., Sehgal, R., Armstrong, J., Higgins-Chen, A. T., Horvath, S., & Wang, B. CpGPT: a foundation model for DNA methylation. bioRxiv 2024.10.24.619766 (2024).", | |
| "citations": 30, | |
| "citations_date": "2026-07-05", | |
| "clock_name": "cpgptpcgrimage3", | |
| "data_type": "DNA methylation", | |
| "doi": "https://doi.org/10.1101/2024.10.24.619766", | |
| "journal": "bioRxiv", | |
| "last_author": "Bo Wang", | |
| "model_type": "PCA + Cox regression", | |
| "n_features": 31, | |
| "notes": "Principal-component CpGPTGrimAge3 implementation combining chronological age, GrimAge2 DNAm proxies, and CpGPT-predicted plasma-protein proxies; 30 proxy inputs are projected to 29 PCs, entered with age into a Cox linear predictor, and calibrated to years.", | |
| "platform": [ | |
| "Illumina 450K" | |
| ], | |
| "population": "adults", | |
| "postprocess": "cox_to_years", | |
| "predicts": [ | |
| "biological age", | |
| "mortality risk" | |
| ], | |
| "preprocess": "scale", | |
| "research_only": true, | |
| "species": "Homo sapiens", | |
| "tissue": [ | |
| "whole blood" | |
| ], | |
| "training_target": [ | |
| "mortality" | |
| ], | |
| "unit": [ | |
| "years" | |
| ], | |
| "version": "0.5.0", | |
| "year": 2024 | |
| } |