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MyHeartCounts/openmhc-dlinear-imp
openmhc-dlinear-imp is a machine learning model from MyHeartCounts. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for openmhc. The card lists the license as openrail.
Reference checkpoint for OpenMHC. Window: daily (1440 minute), 19 sensor channels.
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Updated Jun 7, 2026
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From the Hugging Face model README
Reference checkpoint for OpenMHC. Window: daily (1440 minute), 19 sensor channels.
Wrapper around a PyPOTS-backed imputer trained on the OpenMHC imputation training split. Reconstructs masked sensor windows across 19 channels.
from openmhc.imputers import DLinearImputer
import openmhc
imp = DLinearImputer.from_release("hf://MyHeartCounts/openmhc-dlinear-imp")
results = openmhc.evaluate_imputation(imp, version="xs")
print(results.summary())
Requires the matching optional extras: pip install 'openmhc[pypots,hf]'.
Pin a specific revision with the @ suffix:
DLinearImputer.from_release("hf://MyHeartCounts/[email protected]")
MHC_Dataset/mhc-pypots-dlinear/dlinear:v49openmhc_manifest.json.Released under the OpenRAIL license. See the OpenMHC repository for use restrictions tied to the underlying data agreement.
@misc{openmhc,
title = {OpenMHC: Accelerating the Science of Wearable Foundation Models},
author = {OpenMHC team},
url = {https://github.com/AshleyLab/myheartcounts-dataset}
}