Saspatez/FlashHAR-X

AI model by Saspatez

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Trained model (not a Transformers checkpoint). Custom multiscale 1D-convolution + two-block attention model for classifying smartphone inertial signals. These results are produced by this project's artifacts/officialtestmetrics.csv after completing the notebook, not copied from papers. Other research numbers are only comparable when inputs, split, and metric definitions match. The checkpoint chosen here is the custom-Triton-trained model, not necessarily the highest-scoring baseline. Clone the associated GitHub project and install its inference dependencies, then: The notebook must first have downloaded/extracted the official UCI HAR dataset under data/. The inference script reads…

Saspatez/FlashHAR-X on Hugging Face A short preview, not the full document.

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UCI Human Activity Recognition Using Smartphones

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Model overview

Saspatez/FlashHAR-X is a task-unspecified model repository published by Saspatez on Hugging Face. The source reports the pytorch library.

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Model facts

Task: Not reported
Library: pytorch
Recent downloads (30 days): 0
Cumulative likes: 0
Hugging Face trending score: 0
Reported safetensors parameters: 443,400
Architecture: Not reported
License: Not reported — check the model card
Access: Not gated by Hugging Face
Created: 2026-10-11T06:30:42.000Z
Last modified: 2026-10-11T06:30:50.000Z

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Source: Hugging Face Hub. Metadata observed 2026-10-11T06:41:09.807Z. Daily imports are snapshots, not real-time monitoring.

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