# huggingface/diffusers SLOC report

> As of 2026-09-15 (commit 759164b7ad11), huggingface/diffusers contains 904,647 total lines: 723,760 code, 64,378 comments, 116,509 blank, across 1,649 files in 10 languages (top: Python 99.8%). Custom configuration (tests excluded, docs excluded, generated excluded). Counted with tokei via OctoCounts.

huggingface/diffusers has 723,760 source lines of code out of 904,647 total lines across 1,649 files, counted from the 759164b7ad116e091e9d3e222211c9aa27d835f6 ref at commit 759164b7ad11 by the OctoCounts tokei engine on 2026-09-15. The report is cached by commit, tokei version, and analysis options, so recounting the same revision returns exactly these numbers.

OctoCounts produced this report by resolving huggingface/diffusers to commit 759164b7ad11, 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.

## Repository size insights

This is a large codebase by counted code lines. Code represents 80.0% of all lines, comments represent 7.1%, and the repository averages 439 code lines per file. Python accounts for 99.8% of counted code.

| Language | Files | Lines | Code | Comments | Blanks |
| --- | ---: | ---: | ---: | ---: | ---: |
| Python | 1,467 | 889,445 | 722,481 | 54,765 | 112,199 |
| Jupyter Notebooks | 3 | 1,011 | 715 | 113 | 183 |
| Dockerfile | 7 | 349 | 273 | 23 | 53 |
| Shell | 6 | 153 | 111 | 18 | 24 |
| YAML | 4 | 93 | 82 | 0 | 11 |
| Makefile | 1 | 107 | 60 | 14 | 33 |
| TOML | 2 | 45 | 26 | 8 | 11 |
| Autoconf | 2 | 12 | 12 | 0 | 0 |
| Markdown | 97 | 12,713 | 0 | 8,719 | 3,994 |
| Plain Text | 60 | 719 | 0 | 718 | 1 |

Top language (Python 99.8%). Generated at 2026-09-15T10:19:59.535413862+00:00. Canonical report: https://octocounts.com/github/huggingface/diffusers

## Reproduce this report

[Reproduce this exact report and configuration](https://octocounts.com/github/huggingface/diffusers/commit/759164b7ad116e091e9d3e222211c9aa27d835f6?analysis=%7B%22ignoredDirs%22%3A%5B%5D%2C%22ignoredLanguages%22%3A%5B%5D%2C%22profile%22%3A%22default%22%2C%22includeDocs%22%3Afalse%2C%22includeTests%22%3Afalse%2C%22includeGenerated%22%3Afalse%7D).

## Report FAQ

### How many lines of code does huggingface/diffusers have?

huggingface/diffusers has 904,647 total lines, including 723,760 code lines, 64,378 comment lines, and 116,509 blank lines.

### How was the huggingface/diffusers line count measured?

OctoCounts resolved the public GitHub repository to commit 759164b7ad11, downloaded the source archive, counted it with tokei, and cached the report by commit, tokei version, and analysis options.

### What commit was counted for huggingface/diffusers?

This OctoCounts report was generated from 759164b7ad116e091e9d3e222211c9aa27d835f6 at commit 759164b7ad11 on 2026-09-15T10:19:59.535413862+00:00.

## Similar repository reports

- [rpi-nsl/CRANE](https://octocounts.com/github/rpi-nsl/CRANE) — Python, 719,730 code lines
- [sickn33/antigravity-awesome-skills](https://octocounts.com/github/sickn33/antigravity-awesome-skills) — Python, 736,445 code lines
- [vllm-project/vllm](https://octocounts.com/github/vllm-project/vllm) — Python, 751,628 code lines
- [Significant-Gravitas/AutoGPT](https://octocounts.com/github/Significant-Gravitas/AutoGPT) — Python, 779,969 code lines
- [PrefectHQ/prefect](https://octocounts.com/github/PrefectHQ/prefect) — Python, 650,507 code lines
- [volcengine/OpenViking](https://octocounts.com/github/volcengine/OpenViking) — Python, 624,279 code lines

## Related OctoCounts pages

- [Recently analyzed repositories](https://octocounts.com/recent)
- [Popular SLOC reports](https://octocounts.com/popular)
- [Trending GitHub repositories](https://octocounts.com/trending)
- [Hall of Monoliths](https://octocounts.com/hall-of-monoliths)
- [TensorFlow vs PyTorch](https://octocounts.com/compare/tensorflow-vs-pytorch)
- [Django vs Ruby on Rails](https://octocounts.com/compare/django-vs-rails)
- [Laravel vs Django](https://octocounts.com/compare/laravel-vs-django)
- [GitHub SLOC counter guide](https://octocounts.com/docs/github-sloc-counter)
- [Counting methodology](https://octocounts.com/docs/methodology)
- [SLOC and code metrics glossary](https://octocounts.com/docs/glossary)
- [Original research: how filtering changes SLOC counts](https://octocounts.com/research)
- [OctoCounts API docs](https://octocounts.com/docs/api)
