Abhisheklearn12/inference-cuda-kernels

Abhisheklearn12/inference-cuda-kernels has 662 source lines of code out of 1,003 total lines across 8 files, counted from the main ref at commit e9b0194ade17 by the OctoCounts tokei engine on 2026-09-28. The report is cached by commit, tokei version, and analysis options, so recounting the same revision returns exactly these numbers.

As of 2026-09-28 (commit e9b0194ade17), Abhisheklearn12/inference-cuda-kernels contains 1,003 total lines: 662 code, 229 comments, 112 blank, across 8 files in 3 languages (top: CUDA 95.8%). Custom configuration (tests excluded, docs excluded, generated excluded). Counted with tokei via OctoCounts.

OctoCounts produced this report by resolving Abhisheklearn12/inference-cuda-kernels to commit e9b0194ade17, downloading the repository source archive, and counting every source file with tokei, the open-source line counter written in Rust. The table below breaks the count down by programming language into files, total lines, code lines, comment lines, and blank lines, so the figures can be compared across languages and projects. Results are cached by commit, tokei version, and analysis options, so counting the same revision again reproduces exactly these numbers.

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How many lines of code does Abhisheklearn12/inference-cuda-kernels have?

Abhisheklearn12/inference-cuda-kernels has 1,003 total lines, including 662 code lines, 229 comment lines, and 112 blank lines.

How was the Abhisheklearn12/inference-cuda-kernels line count measured?

OctoCounts resolved the public GitHub repository to commit e9b0194ade17, downloaded the source archive, counted it with tokei, and cached the report by commit, tokei version, and analysis options.

What commit was counted for Abhisheklearn12/inference-cuda-kernels?

This OctoCounts report was generated from main at commit e9b0194ade17 on 2026-09-28T17:25:10.808229456+00:00.