Introduction¶

In model inference and agent development, analyzing the feature distribution of embedding vectors or performing quantization calculations is a common requirement. DeepSeek Harness (DSH) adopts a plugin-based architecture, aiming to extend its capabilities through community plugins. For scenarios that require counting the number of 1s in a vector (Hamming weight), the community provides the dsh-hamming-weight plugin. This plugin is implemented in pure Node and does not depend on external networks, making it suitable for direct use in local or restricted environments.

What Is This¶

dsh-hamming-weight is a DeepSeek Harness plugin focused on Hamming weight calculation. It is maintained by uckkk and categorized under model inference. Its core role is to perform Hamming weight operations on input data without making network requests.

Core Features¶

Based on verified information, the plugin provides the following capabilities:
* Hamming weight calculation
* No network dependency

Installation and Activation¶

Before installation, ensure that your environment meets the dependency requirements. This plugin requires version ^4.0.1 of @deepseek-ai/cordis and version >=0.1.0-rc.6 of @deepseek-ai/dsh-tools.

The installation command is as follows:

dsh plugin add github:uckkk/dsh-hamming-weight

Applicable Scenarios and Notes¶

This plugin is suitable for scenarios where quantization or analysis of vector sparsity is needed during model inference. Note that the plugin runs with the permissions of the current DSH process. Before installing, it is recommended to review the source code and license (MIT).

Conclusion¶

dsh-hamming-weight provides basic Hamming weight calculation capabilities for local inference scenarios and avoids introducing network dependencies. For more details, see the plugin directory or the GitHub repository.