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MyHeartCounts/openmhc-lsm2-weekly
openmhc-lsm2-weekly is a feature extraction model from MyHeartCounts. Use it when you need embeddings to search or compare text. It is set up for openmhc. The card lists the license as openrail.
Reference checkpoint for OpenMHC. Window: weekly (10080 minute, patch 60), 19 sensor channels.
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Updated May 29, 2026
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From the Hugging Face model README
Reference checkpoint for OpenMHC. Window: weekly (10080 minute, patch 60), 19 sensor channels.
An extension of LSM2-daily to 7-day (10080 minute) context. Same masked-autoencoder ViT architecture, but pre-trained on week-long sequences with a larger 60-minute patch size — useful when downstream tasks need multi-day context. Wrapped here for the OpenMHC imputation evaluation track.
from openmhc.imputers import LSM2Imputer
import openmhc
imp = LSM2Imputer.from_release("hf://MyHeartCounts/openmhc-lsm2-weekly")
results = openmhc.evaluate_imputation(imp, version="xs")
print(results.summary())
Requires the matching optional extras: pip install 'openmhc[lsm2,hf]'.
Pin a specific revision with the @ suffix:
LSM2Imputer.from_release("hf://MyHeartCounts/[email protected]")
MHC_Dataset/mhc-mae-ssl/model-o5quh2cd:v2openmhc_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}
}