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  This repository is the official **checkpoint repository** for STEP. It is intended solely for storing the model checkpoints, training logs, and corresponding configuration files (.yaml) used in STEP, to facilitate usage, reproduction, and comparison of Spiking Transformer models by researchers and interested users.
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  For the complete STEP framework, including source code and tutorials, please refer to the [official GitHub repository](https://github.com/Fancyssc/STEP).
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- <!-- Built on top of **[BrainCog](https://github.com/BrainCog-X/Brain-Cog)**, this repository reproduces state-of-the-art Spiking Transformer models and offers a unified pipeline for **classification, segmentation, and object detection**. By standardizing data loaders, training routines, and logging, it enables fair, reproducible comparisons while remaining easy to extend with new models or tasks.
 
 
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  - **Modular Design** – Swap neuron models, encodings, or attention blocks with a few lines of code.
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  - **Multi-Task Ready** – Shared backbone, task-specific heads; evaluate *once*, report *everywhere*.
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  β”‚ β”œβ”€β”€ mmdet
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  β”‚ └── ...
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  └── README.md
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- ``` --> -->
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  ## πŸš€ Quick Start
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  This repository is the official **checkpoint repository** for STEP. It is intended solely for storing the model checkpoints, training logs, and corresponding configuration files (.yaml) used in STEP, to facilitate usage, reproduction, and comparison of Spiking Transformer models by researchers and interested users.
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  For the complete STEP framework, including source code and tutorials, please refer to the [official GitHub repository](https://github.com/Fancyssc/STEP).
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+ <!--
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+ Built on top of **[BrainCog](https://github.com/BrainCog-X/Brain-Cog)**, this repository reproduces state-of-the-art Spiking Transformer models and offers a unified pipeline for **classification, segmentation, and object detection**. By standardizing data loaders, training routines, and logging, it enables fair, reproducible comparisons while remaining easy to extend with new models or tasks.
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  - **Modular Design** – Swap neuron models, encodings, or attention blocks with a few lines of code.
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  - **Multi-Task Ready** – Shared backbone, task-specific heads; evaluate *once*, report *everywhere*.
 
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  β”‚ β”œβ”€β”€ mmdet
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  β”‚ └── ...
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  └── README.md
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+ ``` -->
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  ## πŸš€ Quick Start
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