openmhc-chronos2-fc

OpenMHC Forecasting — Chronos-2

Track 3 (forecasting) reference checkpoint for the MyHeartCounts / OpenMHC wearable-health benchmark.

This checkpoint is a Chronos-2 model. Chronos-2 is Amazon's universal time-series foundation model, supporting multivariate and covariate-informed probabilistic forecasting.

Fine-tuned from the pretrained amazon/chronos-2 base on the MHC training split (LoRA, rank 8, alpha 16; the adapter has been merged into the base so this is a standalone full model — no PEFT runtime dependency).

• Checkpoint format: HuggingFace model directory (checkpoint/: config.json + model.safetensors)
• Forecasting task: 24-hour-ahead, 19 sensor channels, hourly resolution.

Intended use

Intended use: research, methodological comparison, and reproduction of the OpenMHC benchmark.

Out of scope: diagnosis, screening, prognosis, prospective risk prediction, clinical decision support, or any other medical decision-making. OpenMHC's medical condition labels are self-reported and have no diagnosis dates, and benchmark performance does not establish clinical utility. Any diagnostic, prognostic, or screening claim requires independent validation using temporally aligned, clinically adjudicated outcomes in the target population.

Model & implementation

• Chronos (official implementation)
• Base model amazon/chronos-2
• Paper: Chronos-2: From Univariate to Universal Forecasting (Ansari et al., 2025)

Usage

import openmhc
from openmhc.forecasters import Chronos2Forecaster

# pip install "openmhc[chronos]"
fc = Chronos2Forecaster.from_release("hf://MyHeartCounts/[email protected]")
results = openmhc.evaluate_forecasting(fc, version="full")

The same bundle also loads in the evaluation harness via model.release_dir=hf://MyHeartCounts/[email protected]. See openmhc_manifest.json for provenance (training run, base model, fine-tuning details) and architecture metadata.

License

Released under the BigScience OpenRAIL-M license. The use restrictions in its Attachment A apply to this checkpoint and any derivatives; among other things, they prohibit providing medical advice and medical results interpretation.

This checkpoint is fine-tuned from amazon/chronos-2, which is licensed under Apache-2.0; its license and notices continue to apply to the base model.

Citation

If you use this checkpoint, please cite the OpenMHC benchmark and the original Chronos-2 work (linked above).