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MyHeartCounts/
openmhc-toto-fc

Name: openmhc-toto-fc
Availability: InStock

openmhc

time-series-forecasting

wearables

2407.07874

cc-by-4.0

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OpenMHC Forecasting — Toto

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

This checkpoint is a Toto model. Toto (Time-series Optimized Transformer for Observability) is Datadog's decoder-only time-series foundation model with a probabilistic output head.

Fine-tuned (full) from the pretrained Datadog/Toto-Open-Base-1.0 base on the MHC training split.

Checkpoint format: PyTorch Lightning checkpoint (model.ckpt)
Forecasting task: 24-hour-ahead, 19 sensor channels, hourly resolution.

Model & implementation

Usage

python

import openmhc
from openmhc.forecasters import TotoForecaster

# pip install "openmhc[toto]"
fc = TotoForecaster.from_release("hf://MyHeartCounts/openmhc-toto-fc@v1.0")
results = openmhc.evaluate_forecasting(fc, version="full")

The same bundle also loads in the evaluation harness via model.release_dir=hf://MyHeartCounts/openmhc-toto-fc@v1.0. See openmhc_manifest.json for provenance (training run, base model, fine-tuning details) and architecture metadata.

Citation

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