Öffentliches RegisterGut
Software-GesundheitsberichtSchema 0.16.0 · Metriken 1.13.0 · 2026-07-21 01:57 UTC
Dao-AILab / flash-attention
Fast and memory-efficient exact attention
Dao-AILab/flash-attention erreicht einen Gesundheitsindex von 74 von 100 und liegt damit im Bereich Gut. Am stärksten schneidet es bei Vitality (96/100) ab, am schwächsten bei Security (61/100). Zuletzt vor 1 Tag aktualisiert. Ein einzelner Mitwirkender trägt den Großteil der jüngsten Arbeit.
74
gesamt / 100Software-Gesundheitsindex
Metriken werden auf einer Skala von 1–100 in gewichtete Kategorien gruppiert. Der Gesamtwert beginnt als ihr Mittel; sobald öffentliche Evidenz die Richtlinie für Hochrisikojurisdiktionen auslöst, wird die Bewertung angepasst und erhält die Obergrenze 49 (Gefährdet). AI Readiness liegt außerhalb.
74
Exzellent85-100Vorbildlich; erfüllt im Wesentlichen alle geprüften Kriterien
Gut70-84Gesund; geringfügige Lücken
Mittel50-69Akzeptabel mit deutlichen Lücken; Überprüfung empfohlen
Gefährdet30-49Erhebliche Schwächen; eine Übernahme erfordert Vorsicht
Kritisch1-29Schwerwiegende Probleme (aufgegeben, nur ein Maintainer, keine Hygiene)
Bewertungsprofil
Jede Achse ist eine Kategorie. Die Form zählt mehr als der Durchschnitt — ein gesundes Projekt füllt die gesamte Fläche, während ein Profil aus Spitzen und Kratern bedeutet, dass Stärke in einer Dimension Risiken in einer anderen verdeckt.
Eigentümerschaft
Dao AI LabOrganisation
1.517 Follower11 öffentliche Reposseit Juli 2023
Dieses Repository wird von einer Organisation getragen — geteilte, rechenschaftspflichtige Trägerschaft, die jeden einzelnen Maintainer überdauern kann.
Paket-Ökosysteme
| Registry | Paket | Version | Downloads / Monat | Versionen | Zuletzt veröffentlicht |
|---|---|---|---|---|---|
| PyPI | flash-attn-4 | 4.0.0b22 | 1.621.820 | 20 | vor 5 Tagen |
Metriken nach Kategorie
Vitalität
Lebt das Projekt — wird Code geschrieben und werden Releases ausgeliefert?
96
Entwicklungsaktivität
100Exzellent
Wie die Bewertung erfolgt
| 36/36 | Push-Aktualität — letzter Push vor 1 Tagen |
| 36/36 | Commit-Rhythmus — 52/52 Wochen mit Commits |
| 18/18 | Commit-Volumen — 566 Commits im letzten Jahr |
| 10/10 | OpenSSF Scorecard: Maintained — 30 commit(s) and 10 issue activity found in the last 90 days -- score normalized to 10 |
Verwendete Eingangsdaten
| commits_last_year | 566 |
| human_commit_share | — |
| days_since_last_push | 1 |
| active_weeks_last_year | 52 |
Release-Disziplin
90Exzellent
Wie die Bewertung erfolgt
| 27/27 | Liefert Releases aus — 100 Releases veröffentlicht |
| 36/36 | Release-Aktualität — letztes Release vor 5 Tagen |
| 27/27 | Release-Rhythmus — ein Release etwa alle 6,2 Tage |
| 0/10 | OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases. |
Verwendete Eingangsdaten
| releases_count | 100 |
| latest_release_tag | fa4-v4.0.0.beta22 |
| releases_from_tags | nein |
| days_since_latest_release | 5 |
| mean_days_between_releases | 6,2 |
Community & Verbreitung
Hat das Projekt Nutzer, Downloads, Aufmerksamkeit und ein einladendes Umfeld für Beitragende?
81
Popularität & Verbreitung
97Exzellent
Wie die Bewertung erfolgt
| 60/60 | Stars — 24.497 Stars |
| 25/25 | Forks — 2.919 Forks |
| 12.1/15 | Watcher — 151 Watcher |
Verwendete Eingangsdaten
| forks | 2.919 |
| stars | 24.497 |
| watchers | 151 |
| growth_state | unverified |
| growth_factor_pct | 100 |
| growth_unverified_reason | no_history |
Community-Gesundheit
50Mittel
Wie die Bewertung erfolgt
| 22.5/22.5 | README |
| 22.5/22.5 | Lizenz — anerkannte Lizenz (BSD-3-Clause) |
| 0/18 | CONTRIBUTING-Leitfaden |
| 0/13.5 | Verhaltenskodex |
| 0/7.2 | Issue-Vorlage |
| 0/6.3 | PR-Vorlage |
Verwendete Eingangsdaten
| has_readme | ja |
| has_license | ja |
| has_contributing | nein |
| has_issue_template | nein |
| has_code_of_conduct | nein |
| has_pull_request_template | nein |
Ökosystem-Verbreitung (Downloads)
100Exzellent
Wie die Bewertung erfolgt
| 80/80 | Downloads pro Monat — 1.621.820 Downloads/Monat über pypi |
| 0/20 | Abhängige in der Registry — von diesem Ökosystem nicht ausgewiesen |
Verwendete Eingangsdaten
| packages | flash-attn-4 |
| dependents | — |
| ecosystems | pypi |
| total_downloads | — |
| monthly_downloads | 1.621.820 |
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Abhängige in der Registry. Die verbleibenden Gewichte wurden renormalisiert.
Nachhaltigkeit & Governance
Überdauert das Projekt die Menschen, die es tragen — Bus-Faktor, Reaktionsfähigkeit, Trägerschaft und Paketpflege?
64
Maintainer-Resilienz (Bus-Faktor)
40Gefährdet
Wie die Bewertung erfolgt
| 9/54 | Bus-Faktor — 1 Beitragende decken die Hälfte aller Commits ab |
| 7.6/22.5 | Commit-Verteilung — wichtigste beitragende Person verfasste 66 % der Commits |
| 13.5/13.5 | Breite der Beitragenden — 100 Beitragende |
| 10/10 | OpenSSF Scorecard: Contributors — project has 10 contributing companies or organizations |
Verwendete Eingangsdaten
| bus_factor | 1 |
| contributors_sampled | 100 |
| top_contributor_share | 0,663 |
Wie die Bewertung erfolgt
| 20.2/46.8 | Issue-Lösungsquote — 43 % der Issues geschlossen |
| 27/38.3 | PR-Annahme — 483/685 entschiedene PRs gemergt |
| 15/15 | OpenSSF Scorecard: Code-Review — all changesets reviewed |
Verwendete Eingangsdaten
| merged_prs | 483 |
| open_issues | 1.016 |
| closed_issues | 775 |
| issue_closed_ratio | 0,433 |
| closed_unmerged_prs | 202 |
Eigentümerschaft & Trägerschaft
67Mittel
Wie die Bewertung erfolgt
| 30/30 | Organisatorische Trägerschaft — im Besitz einer Organisation |
| 0/20 | Verifizierte Domain |
| 22.9/25 | Reichweite des Inhabers — 1.517 Follower von Dao-AILab |
| 13.9/25 | Kontohistorie — 11 öffentliche Repos, Kontoalter ca. 3 Jahre |
Verwendete Eingangsdaten
| followers | 1.517 |
| owner_type | Organization |
| is_verified | — |
| owner_login | Dao-AILab |
| public_repos | 11 |
| account_age_days | 1.103 |
Paketpflege
100Exzellent
Wie die Bewertung erfolgt
| 25/25 | Veröffentlicht & auflösbar — 1 Paket(e) auf pypi |
| 35/35 | Veröffentlichungsaktualität — letzte Veröffentlichung vor 5 Tagen |
| 20/20 | Versionshistorie — 20 veröffentlichte Versionen |
| 20/20 | Nicht veraltet — aktiv, nicht veraltet oder zurückgezogen |
Verwendete Eingangsdaten
| packages | flash-attn-4 |
| ecosystems | pypi |
| any_deprecated | nein |
| min_days_since_publish | 5 |
Engineering-Qualität
Sind grundlegende Engineering- und Dokumentationspraktiken vorhanden?
66
Wie die Bewertung erfolgt
| 24/24 | CI-Workflows — 6 Workflow(s) |
| 24/24 | Tests vorhanden |
| 16/16 | Linter-Konfiguration — .flake8 |
| 9.6/9.6 | Pre-Commit-Hooks |
| 0/6.4 | .editorconfig |
| 2/20 | OpenSSF Scorecard: CI-Tests — 5 out of 30 merged PRs checked by a CI test -- score normalized to 1 |
Verwendete Eingangsdaten
| has_ci | ja |
| has_tests | ja |
| has_editorconfig | nein |
| has_linter_config | ja |
| has_precommit_config | ja |
Dokumentation
50Mittel
Wie die Bewertung erfolgt
| 30/30 | README |
| 0/25 | Dokumentationsverzeichnis |
| 0/15 | Dokumentations-/Homepage-Site |
| 10/10 | Repository-Beschreibung |
| 0/10 | Topics |
| 10/10 | Wiki |
Verwendete Eingangsdaten
| topics | — |
| has_wiki | ja |
| homepage | — |
| has_readme | ja |
| has_docs_dir | nein |
| has_description | ja |
Sicherheit
Sind die sichtbaren Sicherheits- und Lieferkettenpraktiken belastbar, ohne ungeklärte Exposition gegenüber Hochrisikojurisdiktionen?
61
Sicherheitslage
51Mittel
Wie die Bewertung erfolgt
| 7.5/7.5 | Binary-Artifacts — no binaries found in the repo |
| 0/7.5 | Branch-Protection — keine Daten |
| 0.2/2.5 | CI-Tests — 5 out of 30 merged PRs checked by a CI test -- score normalized to 1 |
| 0/2.5 | CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected |
| 7.5/7.5 | Code-Review — all changesets reviewed |
| 2.5/2.5 | Contributors — project has 10 contributing companies or organizations |
| 10/10 | Dangerous-Workflow — no dangerous workflow patterns detected |
| 0/7.5 | Dependency-Update-Tool — no update tool detected |
| 0/5 | Fuzzing — project is not fuzzed |
| 2.5/2.5 | Lizenz — license file detected |
| 7.5/7.5 | Maintained — 30 commit(s) and 10 issue activity found in the last 90 days -- score normalized to 10 |
| 5/5 | Packaging — packaging workflow detected |
| 0/5 | Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0 |
| 0/5 | SAST — SAST tool is not run on all commits -- score normalized to 0 |
| 0/5 | Security-Policy — security policy file not detected |
| 0/7.5 | Signed-Releases — Project has not signed or included provenance with any releases. |
| 0/7.5 | Token-Permissions — detected GitHub workflow tokens with excessive permissions |
| 7.5/7.5 | Vulnerabilities — 0 existing vulnerabilities detected |
Verwendete Eingangsdaten
| source | openssf_scorecard |
| checks_evaluated | 17 |
| scorecard_version | v5.5.0 |
| checks_inconclusive | 1 |
| scorecard_aggregate | 5,2 |
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): branch_protection. Die verbleibenden Gewichte wurden renormalisiert.
Abhängigkeits-Advisories
100Exzellent
Wie die Bewertung erfolgt
| 35/35 | Direkte Abhängigkeiten ohne bekannte Advisories — keine direkte Abhängigkeit trägt ein bekanntes Advisory |
| 0/25 | Indirekte Abhängigkeiten ohne bekannte Advisories — transitive Menge in diesem Bereich nicht von Entwicklungs- und Test-Abhängigkeiten trennbar |
| 0/40 | Keine offenen Advisories — kein Advisory trägt ein Veröffentlichungsdatum |
Verwendete Eingangsdaten
| source | osv |
| advisories | 0 |
| affected_packages | 0 |
| assessed_packages | 1 |
| unassessed_packages | 7 |
| affected_by_severity | none |
| direct_affected_packages | 0 |
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Indirekte Abhängigkeiten ohne bekannte Advisories, Keine offenen Advisories. Die verbleibenden Gewichte wurden renormalisiert. 1 aufgelöste Abhängigkeiten wurden mit OSV abgeglichen. 7 konnten nicht bewertet werden — keine aufgelöste Version, ein nicht unterstütztes Ökosystem oder außerhalb der ausgewiesenen Paketliste. Dieses Repository veröffentlicht kein Paket, das der Index auflöst; bewertet wurde daher der Abhängigkeitsgraph des Repositorys. Dieser Graph vermischt Entwicklungs- und Test-Pins mit ausgelieferten Abhängigkeiten, daher werden nur die deklarierten Laufzeit-Abhängigkeiten bewertet; transitive Befunde werden als Kontext ausgewiesen und fließen nicht in die Bewertung ein. Erreichbarkeit wird nicht analysiert.
AI Readiness
Wie gut ist das Repository dafür ausgestattet, mit KI-Coding-Agenten entwickelt und gepflegt zu werden? Ein unabhängiges, experimentelles Badge — Gewicht 0,0, es wird eigenständig ausgewiesen und verändert den Gesamt-Gesundheitswert nicht.
66
Wie die Bewertung erfolgt
| 45/45 | Agentenanweisungen — AGENTS.md, CLAUDE.md |
| 0/15 | Maschinenlesbare Doku (llms.txt) |
| 0/40 | Lesbare Commit-Historie — keine Daten |
Verwendete Eingangsdaten
| has_llms_txt | nein |
| legible_history_share | — |
| agent_instruction_files | AGENTS.md, CLAUDE.md |
| agent_instruction_max_bytes | 6.977 |
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Lesbare Commit-Historie. Die verbleibenden Gewichte wurden renormalisiert.
Wie die Bewertung erfolgt
| 18/18 | Bootstrap mit einem Befehl — Makefile |
| 22/22 | Automatisierte Tests |
| 11/11 | Lint-/Format-Konfiguration — .flake8 |
| 0/11 | Statische Typprüfung |
| 10/10 | Reproduzierbare Umgebung — Dockerfile |
| 0/10 | Belegte Agentenpraxis — keine Daten |
| 0/8 | Automatisierte Wartung — keine Daten |
| 0/10 | OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0 |
Verwendete Eingangsdaten
| has_nix | nein |
| has_tests | ja |
| lockfiles | — |
| has_dockerfile | ja |
| typed_language | nein |
| bootstrap_files | Makefile |
| has_devcontainer | nein |
| has_linter_config | ja |
| typecheck_configs | — |
| agent_commit_share | — |
| toolchain_manifests | — |
| dependency_bot_commit_share | — |
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Belegte Agentenpraxis, Automatisierte Wartung. Die verbleibenden Gewichte wurden renormalisiert.
AI-Code-Lesbarkeit für Modelle
50Mittel
Wie die Bewertung erfolgt
| 0/45 | Typprüfbarer Code — Python ohne Typprüfungs-Konfiguration |
| 50.1/55 | Handhabbare Dateigrößen — 26/289 Quelldateien über 60 KB |
Verwendete Eingangsdaten
| primary_language | Python |
| largest_source_bytes | 189.279 |
| source_files_sampled | 289 |
| oversized_source_files | 26 |
Maschinenlesbare AI-Schnittstellen
40Gefährdet
Wie die Bewertung erfolgt
| 0/40 | API-Schema (OpenAPI/GraphQL/proto) |
| 0/20 | MCP-Server |
| 40/40 | Lauffähige Beispiele — examples |
Verwendete Eingangsdaten
| example_dirs | examples |
| has_mcp_signal | nein |
| api_schema_files | — |
Eckdaten
24.497GitHub-Sterne
100Mitwirkende
566Commits, letzte 12 Monate
1Tage seit letztem Push
100Releases
1Bus-Faktor
1.016offene Issues
PyPIPaket-Ökosysteme
Warnungen zur Datenerhebung
- Could not fetch pypi package 'flash_attn_2_cuda' from its registry
- Could not fetch pypi package 'nvcc' from its registry
- Could not fetch pypi package 'dropout_layer_norm' from its registry
- Could not fetch pypi package 'fused_dense_lib' from its registry
- deps.dev does not index pypi:flash-attn-4@4.0.0b22; advisories assessed against the repository dependency graph instead
Weitere Details
OpenSSF Scorecard 5.2 / 10
5.2Gesamtwert
Unabhängige, werkzeugneutrale Sicherheitsbewertung durch das quelloffene OpenSSF Scorecard. Jede Prüfung honoriert eine Sicherheits-Praxis, nicht das Werkzeug eines bestimmten Anbieters. Prüfungen, die Scorecard nicht ermitteln konnte, sind mit k. A. markiert und vom Sicherheitswert ausgeschlossen (nie als null gezählt).
| 10 | Binary-Artifacts | no binaries found in the repo |
| k. A. | Branch-Protection | internal error: error during branchesHandler.setup: internal error: some github tokens can't read classic branch protection rules: https://github.com/ossf/scorecard-action/blob/main/docs/authentication/fine-grained-auth-token.md |
| 1 | CI-Tests | 5 out of 30 merged PRs checked by a CI test -- score normalized to 1 |
| 0 | CII-Best-Practices | no effort to earn an OpenSSF best practices badge detected |
| 10 | Code-Review | all changesets reviewed |
| 10 | Contributors | project has 10 contributing companies or organizations |
| 10 | Dangerous-Workflow | no dangerous workflow patterns detected |
| 0 | Dependency-Update-Tool | no update tool detected |
| 0 | Fuzzing | project is not fuzzed |
| 10 | License | license file detected |
| 10 | Maintained | 30 commit(s) and 10 issue activity found in the last 90 days -- score normalized to 10 |
| 10 | Packaging | packaging workflow detected |
| 0 | Pinned-Dependencies | dependency not pinned by hash detected -- score normalized to 0 |
| 0 | SAST | SAST tool is not run on all commits -- score normalized to 0 |
| 0 | Security-Policy | security policy file not detected |
| 0 | Signed-Releases | Project has not signed or included provenance with any releases. |
| 0 | Token-Permissions | detected GitHub workflow tokens with excessive permissions |
| 10 | Vulnerabilities | 0 existing vulnerabilities detected |
Direkte Abhängigkeiten 7
| Registry | Paket | Versionsvorgabe | Manifest |
|---|---|---|---|
| PyPI | nvidia-cutlass-dsl | ==4.6.0.dev0 | flash_attn/cute/pyproject.toml |
| PyPI | torch | — | flash_attn/cute/pyproject.toml |
| PyPI | einops | — | flash_attn/cute/pyproject.toml |
| PyPI | typing_extensions | — | flash_attn/cute/pyproject.toml |
| PyPI | apache-tvm-ffi | >=0.1.12,<0.2 | flash_attn/cute/pyproject.toml |
| PyPI | torch-c-dlpack-ext | — | flash_attn/cute/pyproject.toml |
| PyPI | quack-kernels | >=0.5.3 | flash_attn/cute/pyproject.toml |
Alle Abhängigkeiten 8
Vollständig aufgelöster Abhängigkeitssatz aus dem GitHub-Abhängigkeitsgraphen: 4 direkte und 4 indirekte (transitive) Pakete. Die transitive Hülle ist vollständig, wenn das Repository eine Lockfile eincheckt.
| Registry | Paket | Version | Beziehung |
|---|---|---|---|
| PyPI | apache-tvm-ffi | — | direkt |
| PyPI | einops | — | direkt |
| PyPI | nvidia-cutlass-dsl | 4.6.0.dev0 | direkt |
| PyPI | quack-kernels | — | direkt |
| PyPI | ninja | — | indirekt |
| PyPI | packaging | — | indirekt |
| PyPI | setuptools | — | indirekt |
| PyPI | setuptools-scm | — | indirekt |
Abhängigkeits-Advisories 0
Dieses Repository veröffentlicht kein vom Index auflösbares Paket, daher wurde sein eigener Abhängigkeitsgraph bewertet – 1 Pakete, darunter auch Entwicklungs- und Test-Pins, die nie ausgeliefert werden: 0 tragen bekannte Advisories, davon 0 direkte. 7 konnten nicht bewertet werden – keine aufgelöste Version, ein nicht unterstütztes Ökosystem, oder außerhalb der ausgewiesenen Paketliste.
Keine bekannten Advisories betreffen die bewerteten Abhängigkeiten.
Ein Advisory bedeutet, dass die im Abhängigkeitsgraphen erfasste Version in den betroffenen Bereich eines Advisories fällt. Erreichbarkeit wird nicht analysiert, und der Graph enthält Entwicklungs- und Test-Pins — ein Fund kann das Werkzeug betreffen und nicht die ausgelieferte Software.
JSON-Rohbericht maschinenlesbar
{
"data": {
"repo": {
"topics": [],
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"size_kb": 21518,
"has_wiki": true,
"homepage": null,
"languages": {
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"C++": 1422396,
"Cuda": 481716,
"Shell": 1749,
"Python": 4552504,
"Makefile": 126,
"Dockerfile": 5305
},
"pushed_at": "2026-07-19T23:09:52Z",
"created_at": "2022-05-19T21:22:06Z",
"owner_type": "Organization",
"updated_at": "2026-07-20T23:53:28Z",
"description": "Fast and memory-efficient exact attention",
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"activity": {
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"has_contributing": false,
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"has_issue_template": false,
"has_code_of_conduct": false,
"has_pull_request_template": false
},
"ecosystem": {
"packages": [
{
"name": "flash-attn-4",
"exists": true,
"license": "BSD 3-Clause License",
"keywords": [
"Development Status :: 3 - Alpha",
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"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12"
],
"ecosystem": "pypi",
"matches_repo": true,
"registry_url": "https://pypi.org/project/flash-attn-4/",
"is_deprecated": false,
"latest_version": "4.0.0b22",
"repository_url": "https://github.com/Dao-AILab/flash-attention",
"versions_count": 20,
"total_downloads": null,
"dependents_count": null,
"deprecation_note": null,
"maintainers_count": null,
"monthly_downloads": 1621820,
"first_published_at": "2026-02-09T17:45:40.785938Z",
"latest_published_at": "2026-07-15T08:51:49.830517Z",
"latest_version_yanked": null,
"days_since_latest_publish": 5
}
]
},
"popularity": {
"forks": 2919,
"stars": 24497,
"watchers": 151,
"open_issues_and_prs": 1216
},
"ai_readiness": {
"has_nix": false,
"example_dirs": [
"examples"
],
"has_llms_txt": false,
"has_dockerfile": true,
"has_mcp_signal": false,
"bootstrap_files": [
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],
"api_schema_files": [],
"has_devcontainer": false,
"typecheck_configs": [],
"largest_source_bytes": 189279,
"source_files_sampled": 289,
"oversized_source_files": 26,
"agent_instruction_files": [
"AGENTS.md",
"CLAUDE.md"
],
"agent_instruction_max_bytes": 6977
},
"dependencies": {
"manifests": [
"flash_attn/pyproject.toml",
"hopper/setup.py",
"setup.py",
"tests/pyproject.toml"
],
"advisories": {
"error": null,
"scope": "repository_graph",
"source": "osv",
"findings": [],
"collected": true,
"truncated": false,
"by_severity": {},
"advisory_count": 0,
"affected_count": 0,
"assessed_count": 1,
"assessed_package": null,
"unassessed_count": 7,
"direct_affected_count": 0
},
"ecosystems": [
"pypi"
],
"dependencies": [
{
"name": "nvidia-cutlass-dsl",
"manifest": "flash_attn/cute/pyproject.toml",
"ecosystem": "pypi",
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"schema_version": "0.16.0",
"badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/d/Dao-AILab/flash-attention.svg",
"full_name": "Dao-AILab/flash-attention",
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"license_spdx": "BSD-3-Clause"
}Bewertungen sind Signale, keine Garantien. Sie spiegeln öffentlich sichtbare Praxis auf GitHub wider — kein Code-Audit und keine Sicherheitsgarantie.
Fehlende Daten werden ausgeschlossen und die Gewichte neu normiert, nie als null bewertet. Die Methodik ist versioniert und offen: Metriken v1.13.0, Schema v0.16.0 — vollständige Methodik · Metriken-Wiki.
Wie ein einzelnes Ergebnis im Gesamtregister steht: aggregierte Statistiken — PyPI.