hlm-micro-har-v1-uci-har

qriton/hlm-micro-har-v1-uci-har

hlm-micro-har-v1-uci-har is a other model from qriton. Use it for the other task on the model card, and read the license before you ship it in a product. It is set up for pytorch. The card lists the license as apache-2.0.

HLM-Micro HAR v1 is a compact polynomial-Hopfield classifier trained on the UCI Human Activity Recognition dataset.

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At a glance

Task: other
Library: pytorch
License: apache-2.0
Access: Public
Created: Jul 13, 2026
Updated: Jul 13, 2026
SHA: 64bf9636

Datasets

uci-har

Model card

From the Hugging Face model README

HLM-Micro HAR v1 - UCI HAR

HLM-Micro HAR v1 is a compact polynomial-Hopfield classifier trained on the UCI Human Activity Recognition dataset.

Results

Field	Value
Parameters	277,760
Classes	6 activities
Reported test accuracy	93.52%
Test windows	2,947 held-out UCI HAR windows
Data	Smartphone IMU activity windows from 30 subjects

Per-class summary from the source evaluation:

Class	Accuracy
Walking	99.60%
Upstairs	98.09%
Downstairs	93.10%
Sitting	90.84%
Standing	95.30%
Laying	84.92%

Files

File	Purpose
`model.pt`	Sanitized model-only PyTorch checkpoint
`config.json`	Public architecture, task, classes, and metric metadata
`metrics.jsonl`	Training/evaluation metrics from the local run

Intended Use

Research on compact human-activity-recognition models.
TinyML and edge-sensor experiments.
Baseline for HLM-Micro architecture comparisons.

Limitations

UCI HAR is a fixed benchmark, not a complete wearable deployment test.
Not a medical, fall-detection, gait-analysis, or safety-critical model.
Production use would require new data collection, calibration, and deployment testing.

Task: other
Library: pytorch
License: apache-2.0
Created: Jul 13, 2026
Updated: Jul 13, 2026