Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-16 20:11 UTC

huggingface / peft

🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.

PythonApache-2.0★ 21,687 stars⑂ 2,506 forkssince Nov 2022View on GitHub ↗

huggingface/peft holds a health index of 98 out of 100, placing it in the Exceptional band. It scores highest on Vitality (95/100) and lowest on Security (78/100). It was last updated today. 2 contributors account for most of its recent work.

98
overall / 100
Exceptional

Software health index

Metrics are grouped into weighted categories on one standardized 1–100 scale. Overall starts as their weighted mean, calibrated against the distribution of the public record so bands carry percentile meaning; when public evidence triggers the High-Risk Jurisdiction Policy, the rating is adjusted and receives an At Risk ceiling of 34.

98
Exceptional93-100The record's top tier (≈ top 5%); essentially all checked criteria met
Excellent80-92Strong across the board; minor gaps
Good65-79Healthy; gaps are limited and manageable
Moderate50-64Acceptable with notable gaps; review recommended
Weak35-49Material weaknesses across several areas
At Risk20-34Significant weaknesses; adoption warrants caution
Critical1-19Severe problems (abandoned, single-maintainer, no hygiene)
VitalityCommunity &AdoptionSustainability &GovernanceEngineeringQualitySecurityAI Readiness

Score profile

Each axis is a category. The shape matters more than the average — a healthy subject fills the whole shape, while a spike-and-crater profile means strength in one dimension is masking risk in another.

The weighted overall 88 is calibrated to 98 on the published index scale (record calibration 2026-08-02).

Ownership

Hugging FaceOrganization · verified domain
68,493 followers467 public repossince Feb 2017

This repository is backed by an organization — shared, accountable stewardship that can outlive any single maintainer.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIpeft0.21.0-371 day agodeeplearning

Metrics by category

Vitality

Is the project alive — is code being written and are releases shipping?

95Exceptional · 21% of overall
How it's scored
36/36Push recency — last push 0 days ago
33.2/36Commit cadence — 48/52 weeks with commits
18/18Commit volume — 476 commits in the last year
0/10OpenSSF Scorecard: Maintained — no data
Inputs used
commits_last_year476
human_commit_share0.98
days_since_last_push0
active_weeks_last_year48
How it's scored
27/27Ships releases — 34 releases published
36/36Release recency — latest release 1 days ago
19.8/27Release cadence — a release every ~57.6 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count34
latest_release_tagv0.21.0
releases_from_tagsno
days_since_latest_release1
mean_days_between_releases57.6

Community & Adoption

Does the project have users, downloads, attention, and a welcoming setup for contributors?

87Excellent · 17% of overall
How it's scored
60/60Stars — 21,687 stars
25/25Forks — 2,506 forks
11.4/15Watchers — 113 watchers
Inputs used
forks2,506
stars21,687
watchers113
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (Apache-2.0)
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges0
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_services—
has_pull_request_templateyes

Sustainability & Governance

Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?

83Excellent · 23% of overall
How it's scored
25.2/54Bus factor — 2 contributor(s) cover half of all commits
14.8/22.5Commit distribution — top contributor authored 34% of commits
13.5/13.5Contributor breadth — 99 contributors
0/10OpenSSF Scorecard: Contributors — no data
Inputs used
bus_factor2
contributors_sampled99
top_contributor_share0.341
How it's scored
40.8/42Issue resolution — 97% of issues closed
23.7/30PR acceptance — 1,622/2,052 decided PRs merged
4/13Newcomer PR acceptance — 4/13 first-time contributors' PRs merged in 30d
0/15OpenSSF Scorecard: Code-Review — no data
Inputs used
merged_prs1,622
open_issues42
closed_issues1,446
prs_merged_7d19
prs_decided_7d34
prs_merged_30d30
prs_decided_30d59
issue_closed_ratio0.972
closed_unmerged_prs430
first_time_authors_30d9
first_time_prs_merged_30d4
first_time_prs_decided_30d13
How it's scored
30/30Ownership backing — organization-owned
20/20Verified domain
25/25Owner reach — 68,493 followers of huggingface
25/25Track record — 467 public repos, account ~9 yr old
Inputs used
followers68,493
owner_typeOrganization
is_verifiedyes
owner_loginhuggingface
public_repos467
account_age_days3,503

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 1 days ago
20/20Version history — 37 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagespeft
ecosystemspypi
any_deprecatedno
min_days_since_publish1

Engineering Quality

Are baseline engineering and documentation practices in place?

95Exceptional · 19% of overall
How it's scored
24/24CI workflows — 16 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff], [tool.black])
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — no data
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://huggingface.co/docs/peft
10/10Repository description
10/10Topics — 10 topics
10/10Wiki
Inputs used
topicsadapter, diffusion, llm, parameter-efficient-learning, python, pytorch, transformers, lora, fine-tuning, peft
has_wikiyes
homepagehttps://huggingface.co/docs/peft
docs_sitehttps://huggingface.co/docs/peft
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

Are visible security and supply-chain practices strong, without unresolved high-risk jurisdiction exposure?

78Good · 16% of overall
How it's scored
30/30Security policy (SECURITY.md)
25/25Dependabot config
0/25Dependency lockfiles — published library — lockfiles are an application concern, not expected
0/20CodeQL workflow
Inputs used
sourcefile_signals
lockfiles—
manifestsmethod_comparison/requirements-app.txt, pyproject.toml, requirements.txt, setup.py
has_codeql_workflowno
has_security_policyyes
has_dependabot_configyes
Excluded from scoring (no data or not applicable): Dependency lockfiles. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisories — no direct dependency carries a known advisory
0/25Indirect dependencies free of known advisories — transitive set not separable from development and test dependencies in this scope
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories65
affected_packages9
assessed_packages16
unassessed_packages55
affected_by_severitycritical 3, high 2, unknown 4
direct_affected_packages0
Excluded from scoring (no data or not applicable): Indirect dependencies free of known advisories, No advisories left outstanding. Remaining weights renormalized. Matched 16 resolved dependencies against OSV. 55 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list. This repository publishes no package the index resolves, so the repository dependency graph was assessed instead. That graph mixes development and test pins with shipped dependencies, so only the declared runtime dependencies are scored; transitive findings are reported as context and excluded from the score. Reachability is not analyzed.

AI Readiness

How well is the repo equipped to be developed and maintained with AI coding agents? Carries a deliberately small weight (4%): agent tooling is a real maintenance signal, but a repository with none can still reach 100/100.

89Excellent · 4% of overall
How it's scored
45/45Agent instructions — .ai/AGENTS.md, AGENTS.md, CLAUDE.md
0/15Machine-readable docs (llms.txt)
40/40Legible commit history — 98 of 98 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share1
agent_instruction_files.ai/AGENTS.md, AGENTS.md, CLAUDE.md
agent_instruction_max_bytes6,226
How it's scored
18/18One-command bootstrap — Makefile, docs/Makefile, method_comparison/MetaMathQA/Makefile, method_comparison/image-gen/Makefile
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff], [tool.black])
11/11Static type checking — src/peft/py.typed
10/10Reproducible environment — Dockerfile
2/10Demonstrated agent practice — 1 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance — 2 of the last 100 commits are automated dependency updates
0/10OpenSSF Scorecard: Pinned-Dependencies — no data
Inputs used
has_nixno
has_testsyes
lockfiles—
has_dockerfileyes
typed_languageno
bootstrap_filesMakefile, docs/Makefile, method_comparison/MetaMathQA/Makefile, method_comparison/image-gen/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configssrc/peft/py.typed
agent_commit_share0.01
toolchain_manifests—
dependency_bot_commit_share0.02
How it's scored
27/45Type-checkable code — Python with type-check config (src/peft/py.typed)
53.2/55Manageable file sizes — 15/446 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes348,751
source_files_sampled446
oversized_source_files15
How it's scored
0/40API schema (OpenAPI/GraphQL/proto) — not applicable to this kind of software
0/20MCP server — not applicable to this kind of software
40/40Runnable examples — examples, notebooks
Inputs used
example_dirsexamples, notebooks
has_mcp_signalno
api_schema_files—
interfaces_expected_of—
Excluded from scoring (no data or not applicable): API schema (OpenAPI/GraphQL/proto), MCP server. Remaining weights renormalized.

Key facts

21,687GitHub stars
99contributors
476commits, last 12 months
0days since last push
34releases
2bus factor
42open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • First-time contributor figures cover 12 of 31 authors (cap 12)
  • pypi download statistics for 'peft' unavailable this scan (stats endpoint failed after retries); adoption may be under-evidenced
  • deps.dev does not index pypi:peft@0.21.0; advisories assessed against the repository dependency graph instead
  • OpenSSF Scorecard did not return a usable result (killed by SIGKILL — most likely the container's memory limit; 2026/09/16 20:09:10 Warning: PATs stored in env variables GITHUB_AUTH_TOKEN and GITHUB_TOKEN differ. Scorecard will use the former.); skipping Scorecard checks

More detail

Star and fork history 0 ★ / 2,506 ⇿
0Stars
2,506Forks
13Releases

When each star and fork was added, collected from GitHub and bucketed by day. Cumulative growth sits directly above the daily additions it is made of, so the two read against each other: steady organic accretion looks nothing like an abrupt, short-lived burst. Where that difference is measurable, it is reported as growth authenticity.

Only the most recent history is shown — this repository exceeds the collection window, so the earliest history is not captured.

1,4001,6001,8002,0002,2002,4002,6002,506102024-102025-092026-09
Major 0Minor 8Patch 5

Each point covers 2 days.

All dependencies 71

Full resolved dependency set from the GitHub dependency graph: 0 direct and 71 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIaccelerate—indirect
PyPIaccelerate1.9.0indirect
PyPIbitsandbytes—indirect
PyPIblack—indirect
PyPIdash—indirect
PyPIdataclass-csv—indirect
PyPIdatasets—indirect
PyPIdatasets2.16.1indirect
PyPIdatasets2.18.0indirect
PyPIdatasets3.6.0indirect
PyPIdatasets4.0.0indirect
PyPIdeepspeed—indirect
PyPIdiffusers—indirect
PyPIdiffusers0.34.0indirect
PyPIdiffusers0.38.0indirect
PyPIeinops—indirect
PyPIevaluate—indirect
PyPIflash-attn—indirect
PyPIgradio—indirect
PyPIgriffe—indirect
PyPIhf-doc-builder—indirect
PyPIhf-transfer—indirect
PyPIhnswlib—indirect
PyPIhuggingface-hub—indirect
PyPIhuggingface-hub0.34.3indirect
PyPIipykernel—indirect
PyPIipywidgets—indirect
PyPIjiwer—indirect
PyPIlibrosa—indirect
PyPImatplotlib—indirect
PyPInb-conda-kernels—indirect
PyPInltk—indirect
PyPInumpy—indirect
PyPIopencv-python4.9.0.80indirect
PyPIpackaging—indirect
PyPIpandas—indirect
PyPIparameterized—indirect
PyPIpeft—indirect
PyPIpillow—indirect
PyPIprotobuf—indirect
PyPIpsutil—indirect
PyPIpyarrow—indirect
PyPIpygithub—indirect
PyPIpytest—indirect
PyPIpytest-cov—indirect
PyPIpytest-xdist—indirect
PyPIpyyaml—indirect
PyPIrequests—indirect
PyPIruff0.16.4indirect
PyPIsafetensors—indirect
PyPIscikit-image0.22.0indirect
PyPIscikit-learn—indirect
PyPIscipy—indirect
PyPIsentencepiece—indirect
PyPIsetuptools—indirect
PyPIsoundfile—indirect
PyPItensorboard—indirect
PyPItiktoken—indirect
PyPItorch—indirect
PyPItorchao—indirect
PyPItorchvision—indirect
PyPItqdm—indirect
PyPItransformers—indirect
PyPItransformers4.52.4indirect
PyPItransformers4.54.0indirect
PyPItransformers4.55.0indirect
PyPIvllm—indirect
PyPIwandb—indirect
PyPIwandb0.16.1indirect
PyPIwandb0.21.0indirect
PyPIxformers—indirect
Dependency advisories 9

This repository publishes no package the index resolves, so its own dependency graph was assessed — 16 packages, which also include development and test pins that never ship: 9 carry known advisories, of which 0 are direct. 55 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list.

PackageVersionRelationSeverityAdvisoriesFixed in
transformers4.52.4indirectcritical245.10.0
transformers4.54.0indirectcritical165.10.0
transformers4.55.0indirectcritical145.10.0
accelerate1.9.0indirecthigh2—
diffusers0.34.0indirecthigh50.38.0
datasets2.16.1indirectunknown15.0.1
datasets2.18.0indirectunknown15.0.1
datasets3.6.0indirectunknown15.0.1
datasets4.0.0indirectunknown15.0.1

An advisory means the version recorded in the dependency graph falls inside an advisory’s affected range. Reachability is not analysed, and the graph includes development and test pins — a finding may concern tooling rather than shipped software.

Raw JSON report machine-readable

Feedback

Spotted something off in this report, or have thoughts to share? Wrong measurements, missed tooling, ideas, questions — anything is welcome. Every message is read and gets a response.

The message is kept through sign-in.

Scores are signals, not warranties. They reflect publicly visible practices on GitHub — not a code audit, and not a security guarantee.

Missing data is excluded and weights renormalized, never scored as zero. Methodology is versioned and open: metrics v2.10.0, schema v0.34.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statistics — PyPI.