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dsh-covariance

Model Inference Updated 2026.08.25

Run the following command in DeepSeek Harness:

dsh plugin install uckkk/dsh-covariance

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

Install the plugin in DeepSeek Harness by running dsh plugin install uckkk/dsh-covariance; the source is available at https://github.com/uckkk/dsh-covariance

About this plugin

Computing a covariance matrix is a critical step in many model inference pipelines, especially when assessing input distributions or sampling quality. Yet a number of existing solutions depend on external services or extra network calls, injecting unnecessary latency and operational complexity into the chain.

dsh-covariance turns that computation into a single, fully local Node.js call. There are no HTTP requests and no external dependency processes: data flows from input to result entirely within the process, making it a natural fit for inference workloads that demand low latency or offline operation.

If you are building a local inference service, passing distribution statistics between nodes, or simply want to remove the uncertainty introduced by a network layer, this plugin keeps covariance computation as straightforward as it gets.

Use Cases

  • Computing input feature covariance matrices in real-time inference pipelines
  • Extracting multivariate distribution statistics in offline environments for sampling
  • Passing covariance data between inference nodes within a single process

Best For

  • Developers building local model inference services
  • Algorithm engineers requiring offline covariance computation
  • System architects pursuing low-latency inference pipelines