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dsh-hamming-weight

Model Inference Updated 2026.08.21

Run the following command in DeepSeek Harness:

dsh plugin install uckkk/dsh-hamming-weight

Paste the following prompt into your AI chat to install this plugin:

In DeepSeek Harness, run dsh plugin install uckkk/dsh-hamming-weight to add the plugin; the source repository is https://github.com/uckkk/dsh-hamming-weight.

About this plugin

Hamming weight — the number of set bits in a binary representation — is a foundational metric in error-correcting codes, cryptographic analysis, and information-theoretic measurements. dsh-hamming-weight packages this computation into a single, plug-and-play dsh plugin command, eliminating the need to hand-roll bit arithmetic or pull in a heavyweight math library. Slipping it into a model-inference pipeline or a data-preprocessing step takes just one line.

The plugin is implemented in pure Node.js with zero network dependencies. It runs identically in offline sandboxes, CI pipelines, and resource-constrained containers, avoiding the usual pitfalls of timeouts, auth tokens, and dependency version drift.

Whether you are validating local encodings, computing bit-vector similarity, or simply need a quick popcount in an inference log, this plugin delivers a zero-config, zero-dependency solution that stays out of your way.

Use Cases

  • Computing popcount inline in inference pipelines
  • Validating Hamming distance in offline ECC workflows
  • Counting set bits in CI pipelines without network access

Best For

  • Inference engineers needing lightweight bit counts
  • Developers in offline or air-gapped environments
  • Researchers in cryptography or coding theory