Request permission to use InferenceX benchmark results in ConfigIQ

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文档
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python, pytorch

调研方向

This is a licensing and permission question rather than a code change: the issue asks whether SemiAnalysis approves private storage, public attributed display, and weekly API refresh of benchmark results, and it points to the API docs and Section 7 of the general terms. A newcomer would read the linked terms and API documentation and check for any stated license, attribution or rate-limit rules. Done means a maintainer has answered the permission question in the thread.

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描述

Hi InferenceX team,

The ConfigIQ team is developing a Compare page that shows measured inference performance alongside AISimulators predictions across concurrency levels.

We would like to add InferenceX as a separately labeled measurement source on ConfigIQ’s comparison page. If approved, we propose to:

  1. Fetch selected published single-turn 8192-input / 1024-output-token results using /api/v1/availability, /api/v1/views/options, and /api/v1/benchmarks.
  2. Normalize the selected results and store them in a private Hugging Face dataset so ConfigIQ can load configuration options.
  3. Display selected measurements on ConfigIQ’s public comparison charts alongside our measurements and AISimulators predictions. We would clearly attribute the data to InferenceX/SemiAnalysis and link to the original benchmark runs. The private dataset would not be offered as a public download.
  4. Refresh the private dataset from your API approximately once a week.

The API documentation describes accessing and exporting data for analysis, but we could not determine whether it permits this specific workflow. Section 7 of SemiAnalysis’s general terms also raises a question about scheduled API collection.

Would SemiAnalysis approve these uses: private storage of a normalized subset, public display of selected measurements with attribution, and a weekly API refresh? Are there license, attribution, or request-frequency requirements we should follow? Thanks.

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  3. Fork 仓库,在一个分支上完成修改。
  4. 提交 Pull Request,并在描述里引用这个 Issue 编号。

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