[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"extension-plugin-huggingface-hf-cli-de":3,"guides-for-huggingface-hf-cli":743,"similar-k172m7ench1yy64c6nbcx5pmm586mphh-de":744},{"_creationTime":4,"_id":5,"children":6,"community":7,"display":9,"evaluation":14,"identity":254,"isFallback":251,"parentExtension":258,"providers":290,"relations":294,"repo":295,"tags":741,"workflow":742},1778690773482.4841,"k172m7ench1yy64c6nbcx5pmm586mphh",[],{"reviewCount":8},0,{"description":10,"installMethods":11,"name":12,"sourceUrl":13},"Execute Hugging Face Hub operations using the hf CLI. Download models/datasets, upload files, manage repos, and run cloud compute jobs.",{"claudeCode":12},"hf-cli","https://github.com/huggingface/skills",{"_creationTime":15,"_id":16,"extensionId":5,"locale":17,"result":18,"trustSignals":235,"workflow":252},1778690967596.5278,"kn711jjm2qrywkq64dn4yh7cb986mrak","en",{"checks":19,"evaluatedAt":203,"extensionSummary":204,"features":205,"nonGoals":211,"promptVersionExtension":215,"promptVersionScoring":216,"purpose":217,"rationale":218,"score":219,"summary":220,"tags":221,"targetMarket":228,"tier":229,"useCases":230},[20,25,28,31,35,38,42,46,49,52,56,60,64,68,71,74,77,80,83,86,90,94,98,102,106,109,112,115,119,122,125,128,131,134,137,141,145,149,152,156,159,162,165,168,170,173,176,179,182,185,189,192,195,199],{"category":21,"check":22,"severity":23,"summary":24},"Practical Utility","Problem relevance","pass","The description clearly states the problem of executing Hugging Face Hub operations using the hf CLI, covering common tasks like downloading models and managing repos.",{"category":21,"check":26,"severity":23,"summary":27},"Unique selling proposition","The plugin provides a dedicated CLI interface for Hugging Face Hub operations, offering a streamlined and integrated experience beyond just calling the underlying `hf` commands directly.",{"category":21,"check":29,"severity":23,"summary":30},"Production readiness","The plugin appears production-ready, as it directly wraps a mature CLI tool ('hf') and covers a comprehensive set of operations for managing Hugging Face Hub resources.",{"category":32,"check":33,"severity":23,"summary":34},"Scope","Single responsibility principle","The plugin focuses solely on Hugging Face Hub operations via the `hf` CLI, adhering to a single domain and avoiding unrelated capabilities.",{"category":32,"check":36,"severity":23,"summary":37},"Description quality","The displayed description accurately reflects the plugin's functionality, covering key operations like downloading, uploading, and managing repos.",{"category":39,"check":40,"severity":23,"summary":41},"Invocation","Scoped tools","The plugin exposes a well-defined set of specific `hf` commands, each acting as a narrow verb-noun specialist, rather than a single generalist tool.",{"category":43,"check":44,"severity":23,"summary":45},"Documentation","Configuration & parameter reference","The SKILL.md file provides comprehensive documentation for all `hf` commands and their parameters, including common options and tips.",{"category":32,"check":47,"severity":23,"summary":48},"Tool naming","The tool names directly correspond to the `hf` CLI commands, which are descriptive and follow standard command-line conventions.",{"category":32,"check":50,"severity":23,"summary":51},"Minimal I/O surface","The plugin's tools, mirroring the `hf` CLI, adhere to minimal I/O by accepting structured flags and returning specific command outputs, not diagnostic dumps.",{"category":53,"check":54,"severity":23,"summary":55},"License","License usability","The plugin is licensed under the Apache-2.0 license, as indicated by the bundled LICENSE file and confirmed by trust signals.",{"category":57,"check":58,"severity":23,"summary":59},"Maintenance","Commit recency","The last commit was on 2026-05-12, indicating recent maintenance activity.",{"category":57,"check":61,"severity":62,"summary":63},"Dependency Management","not_applicable","No third-party dependencies were detected for this plugin beyond the `hf` CLI itself, which is a user-installed prerequisite.",{"category":65,"check":66,"severity":23,"summary":67},"Security","Secret Management","The `hf` CLI handles secrets via tokens, managed through `hf auth login`, which is standard practice and not embedded in committed code. The plugin itself does not manage secrets directly.",{"category":65,"check":69,"severity":23,"summary":70},"Injection","The plugin acts as a wrapper around the `hf` CLI, which is assumed to handle input sanitization; there are no indications of remote data being treated as instructions.",{"category":65,"check":72,"severity":23,"summary":73},"Transitive Supply-Chain Grenades","The plugin relies on the locally installed `hf` CLI and does not fetch external scripts or content at runtime.",{"category":65,"check":75,"severity":23,"summary":76},"Sandbox Isolation","The plugin executes the `hf` CLI, which operates within the user's project context and does not modify files outside of the specified Hugging Face Hub operations.",{"category":65,"check":78,"severity":23,"summary":79},"Sandbox escape primitives","The plugin does not contain any scripts or hooks that would facilitate sandbox escape primitives.",{"category":65,"check":81,"severity":23,"summary":82},"Data Exfiltration","The plugin's operations are limited to interacting with the Hugging Face Hub via the CLI; there are no undocumented outbound calls or submissions of confidential data.",{"category":65,"check":84,"severity":23,"summary":85},"Hidden Text Tricks","The bundled README and SKILL.md files do not contain any hidden text tricks or suspicious Unicode characters.",{"category":87,"check":88,"severity":23,"summary":89},"Hooks","Opaque code execution","The plugin does not contain any opaque code execution mechanisms; it directly invokes the `hf` CLI.",{"category":91,"check":92,"severity":23,"summary":93},"Portability","Structural Assumption","The plugin relies on the user having the `hf` CLI installed, which is a documented prerequisite, and does not make assumptions about project structure beyond that.",{"category":95,"check":96,"severity":23,"summary":97},"Trust","Issues Attention","In the last 90 days, 4 issues were opened and 6 were closed, indicating active maintenance and a closure rate of 60%.",{"category":99,"check":100,"severity":23,"summary":101},"Versioning","Release Management","The `hf-cli` skill has a specific versioning mentioned ('huggingface_hub v1.14.0') and the plugin is frequently updated, as indicated by recent commits.",{"category":103,"check":104,"severity":23,"summary":105},"Code Execution","Validation","The plugin interfaces with the `hf` CLI, which is expected to perform its own input validation for commands and parameters.",{"category":65,"check":107,"severity":23,"summary":108},"Unguarded Destructive Operations","Destructive operations through the `hf` CLI are typically guarded by confirmations or require explicit commands, and the plugin simply wraps these.",{"category":103,"check":110,"severity":23,"summary":111},"Error Handling","The plugin relies on the `hf` CLI for error handling, which provides structured error messages and exit codes.",{"category":103,"check":113,"severity":23,"summary":114},"Logging","The plugin itself does not perform destructive actions or outbound calls beyond invoking the `hf` CLI, which has its own logging mechanisms.",{"category":116,"check":117,"severity":23,"summary":118},"Compliance","GDPR","The plugin operates on Hugging Face Hub resources and does not directly handle personal data without user authentication and explicit operations.",{"category":116,"check":120,"severity":23,"summary":121},"Target market","The plugin's functionality is globally applicable to the Hugging Face Hub and has no regional restrictions.",{"category":91,"check":123,"severity":23,"summary":124},"Runtime stability","The plugin relies on the `hf` CLI, which is designed to be cross-platform, ensuring runtime stability across different operating systems.",{"category":43,"check":126,"severity":23,"summary":127},"README","The README file is comprehensive, clearly states the plugin's purpose, and provides installation and usage instructions.",{"category":32,"check":129,"severity":23,"summary":130},"Tool surface size","The plugin exposes a large number of `hf` CLI commands, but they are logically grouped and well-documented, fitting within expected complexity for a CLI wrapper.",{"category":39,"check":132,"severity":23,"summary":133},"Overlapping near-synonym tools","While the underlying `hf` CLI has many commands, they are generally distinct, and the plugin exposes them as such without significant overlap in function names.",{"category":43,"check":135,"severity":23,"summary":136},"Phantom features","All features mentioned in the README, particularly regarding the `hf` CLI's capabilities, are directly implemented through the CLI commands.",{"category":138,"check":139,"severity":23,"summary":140},"Install","Installation instruction","The README provides clear installation instructions for various platforms (Claude Code, Codex, Gemini CLI, Cursor) and includes copy-pasteable examples.",{"category":142,"check":143,"severity":23,"summary":144},"Errors","Actionable error messages","The plugin relies on the `hf` CLI for error messages, which are generally actionable and provide guidance on remediation.",{"category":146,"check":147,"severity":62,"summary":148},"Execution","Pinned dependencies","The plugin itself does not have direct dependencies beyond the user's locally installed `hf` CLI.",{"category":32,"check":150,"severity":23,"summary":151},"Dry-run preview","The `hf` CLI includes `--dry-run` options for several commands, which the plugin exposes, allowing users to preview intended effects.",{"category":153,"check":154,"severity":23,"summary":155},"Protocol","Idempotent retry & timeouts","The plugin relies on the `hf` CLI, which handles its own operations; no explicit remote calls or state-changing operations by the plugin itself require custom idempotency or timeouts.",{"category":116,"check":157,"severity":23,"summary":158},"Telemetry opt-in","The plugin is a wrapper around the `hf` CLI and does not appear to have its own telemetry; the `hf` CLI itself does not collect telemetry by default.",{"category":39,"check":160,"severity":23,"summary":161},"Name collisions","The plugin consolidates Hugging Face CLI commands; there are no apparent name collisions with Claude Code built-ins or other skills.",{"category":39,"check":163,"severity":62,"summary":164},"Hooks-off mechanism","This plugin is a direct CLI wrapper and does not utilize hooks, thus a hooks-off mechanism is not applicable.",{"category":39,"check":166,"severity":62,"summary":167},"Hook matcher tightness","This plugin does not use hooks, so this check is not applicable.",{"category":65,"check":169,"severity":62,"summary":167},"Hook security",{"category":87,"check":171,"severity":62,"summary":172},"Silent prompt rewriting","This plugin does not utilize prompt rewriting hooks.",{"category":65,"check":174,"severity":62,"summary":175},"Permission Hook","This plugin does not use permission hooks.",{"category":116,"check":177,"severity":62,"summary":178},"Hook privacy","This plugin does not utilize hooks for logging or telemetry.",{"category":103,"check":180,"severity":62,"summary":181},"Hook dependency","This plugin does not rely on external hook scripts.",{"category":43,"check":183,"severity":23,"summary":184},"Feature Transparency","All functionalities are transparently mapped to `hf` CLI commands, as documented in the README and SKILL.md.",{"category":186,"check":187,"severity":23,"summary":188},"Convention","Layout convention adherence","The plugin structure follows standard conventions, with the `hf-cli` skill and its associated `SKILL.md` located within the expected directory structure.",{"category":186,"check":190,"severity":62,"summary":191},"Plugin state","This plugin does not appear to manage persistent state that would need to live under `${CLAUDE_PLUGIN_DATA}`.",{"category":65,"check":193,"severity":62,"summary":194},"Keychain-stored secrets","The plugin relies on the `hf` CLI for authentication, which uses standard token management, not `userConfig` for sensitive secrets.",{"category":196,"check":197,"severity":62,"summary":198},"Dependencies","Tagged release sourcing","The plugin is a direct wrapper around the `hf` CLI, which is installed separately and not bundled as a dependency with a specific source declaration.",{"category":200,"check":201,"severity":23,"summary":202},"Installation","Clean uninstall","The plugin does not install any background daemons or services that would persist after uninstallation.",1778690967203,"This plugin provides access to the Hugging Face Hub CLI (`hf`) for managing models, datasets, spaces, jobs, and more. It acts as a direct interface to the installed `hf` CLI, allowing users to perform a wide range of operations without needing to manually manage CLI commands.",[206,207,208,209,210],"Execute all `hf` CLI commands","Download and upload models/datasets","Manage Hugging Face repositories and spaces","Run and schedule jobs on Hugging Face infrastructure","Manage authentication and cache",[212,213,214],"Replacing the need to install the `hf` CLI separately.","Providing direct Python API access to Hugging Face Hub services.","Managing local development environments unrelated to Hugging Face Hub operations.","3.0.0","4.4.0","To enable AI agents to seamlessly interact with the Hugging Face Hub for managing ML assets, running jobs, and configuring services.","High quality plugin wrapping a mature CLI tool with comprehensive documentation and recent maintenance. All checks passed or were not applicable.",99,"A high-quality plugin providing comprehensive access to Hugging Face Hub operations via the `hf` CLI.",[222,223,224,225,226,227],"huggingface","cli","developer-tools","mlops","datasets","models","global","verified",[231,232,233,234],"When needing to download specific models or datasets from the Hugging Face Hub.","When managing Hugging Face repositories, including creating, deleting, or updating them.","When scheduling or running machine learning jobs on Hugging Face infrastructure.","When setting up or configuring Hugging Face Spaces for demos or applications.",{"codeQuality":236,"collectedAt":238,"documentation":239,"maintenance":242,"security":248,"testCoverage":250},{"hasLockfile":237},false,1778690943634,{"descriptionLength":240,"readmeSize":241},135,9821,{"closedIssues90d":243,"forks":244,"hasChangelog":237,"openIssues90d":245,"pushedAt":246,"stars":247},6,663,4,1778593131000,10482,{"hasNpmPackage":237,"license":249,"smitheryVerified":237},"Apache-2.0",{"hasCi":251,"hasTests":237},true,{"updatedAt":253},1778690967596,{"basePath":255,"githubOwner":222,"githubRepo":256,"locale":17,"slug":12,"type":257},"skills/hf-cli","skills","plugin",{"_creationTime":259,"_id":260,"community":261,"display":262,"identity":267,"parentExtension":270,"providers":271,"relations":284,"tags":286,"workflow":287},1778690773482.4824,"k17es3r8wd37t5rrwqcpp5kwrh86mxx8",{"reviewCount":8},{"description":263,"installMethods":264,"name":266,"sourceUrl":13},"Agent Skills for AI/ML tasks including dataset creation, model training, evaluation, and research paper publishing on Hugging Face Hub",{"claudeCode":265},"huggingface/skills","huggingface-skills",{"basePath":268,"githubOwner":222,"githubRepo":256,"locale":17,"slug":256,"type":269},"","marketplace",null,{"evaluate":272,"extract":278},{"promptVersionExtension":273,"promptVersionScoring":216,"score":274,"tags":275,"targetMarket":228,"tier":229},"3.1.0",95,[276,222,226,227,277,224],"ai-ml","research",{"commitSha":279,"marketplace":280,"plugin":282},"HEAD",{"name":266,"pluginCount":281},14,{"mcpCount":8,"provider":283,"skillCount":8},"classify",{"repoId":285},"kd72xwt5xnc0ktc4p7smzfcp3986m959",[276,226,224,222,227,277],{"evaluatedAt":288,"extractAt":289,"updatedAt":288},1778690814090,1778690773482,{"evaluate":291,"extract":293},{"promptVersionExtension":215,"promptVersionScoring":216,"score":219,"tags":292,"targetMarket":228,"tier":229},[222,223,224,225,226,227],{"commitSha":279},{"parentExtensionId":260,"repoId":285},{"_creationTime":296,"_id":285,"identity":297,"providers":298,"workflow":737},1778689536128.5474,{"githubOwner":222,"githubRepo":256,"sourceUrl":13},{"classify":299,"discover":730,"github":733},{"commitSha":279,"extensions":300},[301,314,323,331,339,347,355,363,368,376,384,392,400,408,416,424,467,476,482,488,505,511,518,560,571,590,596,616,628,652,710],{"basePath":268,"description":263,"displayName":266,"installMethods":302,"rationale":303,"selectedPaths":304,"source":313,"sourceLanguage":17,"type":269},{"claudeCode":265},"marketplace.json at .claude-plugin/marketplace.json",[305,308,310],{"path":306,"priority":307},".claude-plugin/marketplace.json","mandatory",{"path":309,"priority":307},"README.md",{"path":311,"priority":312},"LICENSE","high","rule",{"basePath":315,"description":316,"displayName":317,"installMethods":318,"rationale":319,"selectedPaths":320,"source":313,"sourceLanguage":17,"type":257},"skills/huggingface-llm-trainer","Train or fine-tune language models using TRL on Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes hardware selection, cost estimation, Trackio monitoring, and Hub persistence.","huggingface-llm-trainer",{"claudeCode":317},"inline plugin source from marketplace.json at skills/huggingface-llm-trainer",[321],{"path":322,"priority":312},"SKILL.md",{"basePath":324,"description":325,"displayName":326,"installMethods":327,"rationale":328,"selectedPaths":329,"source":313,"sourceLanguage":17,"type":257},"skills/huggingface-local-models","Use to select models to run locally with llama.cpp and GGUF on CPU, Mac Metal, CUDA, or ROCm. Covers finding GGUFs, quant selection, running servers, exact GGUF file lookup, conversion, and OpenAI-compatible local serving.","huggingface-local-models",{"claudeCode":326},"inline plugin source from marketplace.json at skills/huggingface-local-models",[330],{"path":322,"priority":312},{"basePath":332,"description":333,"displayName":334,"installMethods":335,"rationale":336,"selectedPaths":337,"source":313,"sourceLanguage":17,"type":257},"skills/huggingface-paper-publisher","Publish and manage research papers on Hugging Face Hub. Supports creating paper pages, linking papers to models/datasets, claiming authorship, and generating professional markdown-based research articles.","huggingface-paper-publisher",{"claudeCode":334},"inline plugin source from marketplace.json at skills/huggingface-paper-publisher",[338],{"path":322,"priority":312},{"basePath":340,"description":341,"displayName":342,"installMethods":343,"rationale":344,"selectedPaths":345,"source":313,"sourceLanguage":17,"type":257},"skills/huggingface-papers","Look up and read Hugging Face paper pages in markdown, and use the papers API for structured metadata like authors, linked models, datasets, Spaces, and media URLs when needed.","huggingface-papers",{"claudeCode":342},"inline plugin source from marketplace.json at skills/huggingface-papers",[346],{"path":322,"priority":312},{"basePath":348,"description":349,"displayName":350,"installMethods":351,"rationale":352,"selectedPaths":353,"source":313,"sourceLanguage":17,"type":257},"skills/huggingface-community-evals","Add and manage evaluation results in Hugging Face model cards. Supports extracting eval tables from README content, importing scores from Artificial Analysis API, and running custom evaluations with vLLM/lighteval.","huggingface-community-evals",{"claudeCode":350},"inline plugin source from marketplace.json at skills/huggingface-community-evals",[354],{"path":322,"priority":312},{"basePath":356,"description":357,"displayName":358,"installMethods":359,"rationale":360,"selectedPaths":361,"source":313,"sourceLanguage":17,"type":257},"skills/huggingface-best","Find the best AI model for any task by querying Hugging Face leaderboards and benchmarks. Recommends top models based on task type, hardware constraints, and benchmark scores.","huggingface-best",{"claudeCode":358},"inline plugin source from marketplace.json at skills/huggingface-best",[362],{"path":322,"priority":312},{"basePath":255,"description":10,"displayName":12,"installMethods":364,"rationale":365,"selectedPaths":366,"source":313,"sourceLanguage":17,"type":257},{"claudeCode":12},"inline plugin source from marketplace.json at skills/hf-cli",[367],{"path":322,"priority":312},{"basePath":369,"description":370,"displayName":371,"installMethods":372,"rationale":373,"selectedPaths":374,"source":313,"sourceLanguage":17,"type":257},"skills/huggingface-trackio","Track and visualize ML training experiments with Trackio. Log metrics via Python API and retrieve them via CLI. Supports real-time dashboards synced to HF Spaces.","huggingface-trackio",{"claudeCode":371},"inline plugin source from marketplace.json at skills/huggingface-trackio",[375],{"path":322,"priority":312},{"basePath":377,"description":378,"displayName":379,"installMethods":380,"rationale":381,"selectedPaths":382,"source":313,"sourceLanguage":17,"type":257},"skills/huggingface-datasets","Explore, query, and extract data from any Hugging Face dataset using the Dataset Viewer REST API and npx tooling. Zero Python dependencies — covers split/config discovery, row pagination, text search, filtering, SQL via parquetlens, and dataset upload via CLI.","huggingface-datasets",{"claudeCode":379},"inline plugin source from marketplace.json at skills/huggingface-datasets",[383],{"path":322,"priority":312},{"basePath":385,"description":386,"displayName":387,"installMethods":388,"rationale":389,"selectedPaths":390,"source":313,"sourceLanguage":17,"type":257},"skills/huggingface-tool-builder","Build reusable scripts for Hugging Face Hub and API workflows. Useful for chaining API calls, enriching Hub metadata, or automating repeated tasks.","huggingface-tool-builder",{"claudeCode":387},"inline plugin source from marketplace.json at skills/huggingface-tool-builder",[391],{"path":322,"priority":312},{"basePath":393,"description":394,"displayName":395,"installMethods":396,"rationale":397,"selectedPaths":398,"source":313,"sourceLanguage":17,"type":257},"skills/huggingface-gradio","Build Gradio web UIs and demos in Python. Use when creating or editing Gradio apps, components, event listeners, layouts, or chatbots.","huggingface-gradio",{"claudeCode":395},"inline plugin source from marketplace.json at skills/huggingface-gradio",[399],{"path":322,"priority":312},{"basePath":401,"description":402,"displayName":403,"installMethods":404,"rationale":405,"selectedPaths":406,"source":313,"sourceLanguage":17,"type":257},"skills/transformers-js","Run state-of-the-art machine learning models directly in JavaScript/TypeScript for NLP, computer vision, audio processing, and multimodal tasks. Works in Node.js and browsers with WebGPU/WASM using Hugging Face models.","transformers-js",{"claudeCode":403},"inline plugin source from marketplace.json at skills/transformers-js",[407],{"path":322,"priority":312},{"basePath":409,"description":410,"displayName":411,"installMethods":412,"rationale":413,"selectedPaths":414,"source":313,"sourceLanguage":17,"type":257},"skills/huggingface-vision-trainer","Train and fine-tune object detection models (RTDETRv2, YOLOS, DETR and others) and image classification models (timm and transformers models — MobileNetV3, MobileViT, ResNet, ViT/DINOv3) using Transformers Trainer API on Hugging Face Jobs infrastructure or locally. Includes COCO dataset format support, Albumentations augmentation, mAP/mAR metrics, trackio tracking, hardware selection, and Hub persistence.","huggingface-vision-trainer",{"claudeCode":411},"inline plugin source from marketplace.json at skills/huggingface-vision-trainer",[415],{"path":322,"priority":312},{"basePath":417,"description":418,"displayName":419,"installMethods":420,"rationale":421,"selectedPaths":422,"source":313,"sourceLanguage":17,"type":257},"skills/train-sentence-transformers","Train or fine-tune sentence-transformers models across all three architectures: SentenceTransformer (bi-encoder embeddings), CrossEncoder (rerankers), and SparseEncoder (SPLADE). Covers loss selection, hard-negative mining, evaluators, distillation, LoRA, Matryoshka, and Hugging Face Hub publishing.","train-sentence-transformers",{"claudeCode":419},"inline plugin source from marketplace.json at skills/train-sentence-transformers",[423],{"path":322,"priority":312},{"basePath":268,"description":263,"displayName":266,"installMethods":425,"license":249,"rationale":426,"selectedPaths":427,"source":313,"sourceLanguage":17,"type":257},{"claudeCode":266},"plugin manifest at .claude-plugin/plugin.json",[428,430,431,432,435,437,439,441,443,445,447,449,451,453,455,457,459,461,463,465],{"path":429,"priority":307},".claude-plugin/plugin.json",{"path":309,"priority":307},{"path":311,"priority":312},{"path":433,"priority":434},"skills/hf-cli/SKILL.md","medium",{"path":436,"priority":434},"skills/huggingface-best/SKILL.md",{"path":438,"priority":434},"skills/huggingface-community-evals/SKILL.md",{"path":440,"priority":434},"skills/huggingface-datasets/SKILL.md",{"path":442,"priority":434},"skills/huggingface-gradio/SKILL.md",{"path":444,"priority":434},"skills/huggingface-llm-trainer/SKILL.md",{"path":446,"priority":434},"skills/huggingface-local-models/SKILL.md",{"path":448,"priority":434},"skills/huggingface-paper-publisher/SKILL.md",{"path":450,"priority":434},"skills/huggingface-papers/SKILL.md",{"path":452,"priority":434},"skills/huggingface-tool-builder/SKILL.md",{"path":454,"priority":434},"skills/huggingface-trackio/SKILL.md",{"path":456,"priority":434},"skills/huggingface-vision-trainer/SKILL.md",{"path":458,"priority":434},"skills/train-sentence-transformers/SKILL.md",{"path":460,"priority":434},"skills/transformers-js/SKILL.md",{"path":462,"priority":307},".mcp.json",{"path":464,"priority":312},"agents/AGENTS.md",{"path":466,"priority":312},".cursor-plugin/plugin.json",{"basePath":468,"description":469,"displayName":470,"installMethods":471,"rationale":472,"selectedPaths":473,"source":313,"sourceLanguage":17,"type":475},"hf-mcp/skills/hf-mcp","Use Hugging Face Hub via MCP server tools. Search models, datasets, Spaces, papers. Get repo details, fetch documentation, run compute jobs, and use Gradio Spaces as AI tools. Available when connected to the HF MCP server.","hf-mcp",{"claudeCode":265},"SKILL.md frontmatter at hf-mcp/skills/hf-mcp/SKILL.md",[474],{"path":322,"priority":307},"skill",{"basePath":255,"description":477,"displayName":12,"installMethods":478,"rationale":479,"selectedPaths":480,"source":313,"sourceLanguage":17,"type":475},"Hugging Face Hub CLI (`hf`) for downloading, uploading, and managing models, datasets, spaces, buckets, repos, papers, jobs, and more on the Hugging Face Hub. Use when: handling authentication; managing local cache; managing Hugging Face Buckets; running or scheduling jobs on Hugging Face infrastructure; managing Hugging Face repos; discussions and pull requests; browsing models, datasets and spaces; reading, searching, or browsing academic papers; managing collections; querying datasets; configuring spaces; setting up webhooks; or deploying and managing HF Inference Endpoints. Make sure to use this skill whenever the user mentions 'hf', 'huggingface', 'Hugging Face', 'huggingface-cli', or 'hugging face cli', or wants to do anything related to the Hugging Face ecosystem and to AI and ML in general. Also use for cloud storage needs like training checkpoints, data pipelines, or agent traces. Use even if the user doesn't explicitly ask for a CLI command. Replaces the deprecated `huggingface-cli`.",{"claudeCode":265},"SKILL.md frontmatter at skills/hf-cli/SKILL.md",[481],{"path":322,"priority":307},{"basePath":356,"description":483,"displayName":358,"installMethods":484,"rationale":485,"selectedPaths":486,"source":313,"sourceLanguage":17,"type":475},"Use when the user asks about finding the best, top, or recommended model for a task, wants to know what AI model to use, or wants to compare models by benchmark scores. Triggers on: \"best model for X\", \"what model should I use for\", \"top models for [task]\", \"which model runs on my laptop/machine/device\", \"recommend a model for\", \"what LLM should I use for\", \"compare models for\", \"what's state of the art for\", or any question about choosing an AI model for a specific use case. Always use this skill when the user wants model recommendations or comparisons, even if they don't explicitly mention HuggingFace or benchmarks.\n",{"claudeCode":265},"SKILL.md frontmatter at skills/huggingface-best/SKILL.md",[487],{"path":322,"priority":307},{"basePath":348,"description":489,"displayName":350,"installMethods":490,"rationale":491,"selectedPaths":492,"source":313,"sourceLanguage":17,"type":475},"Run evaluations for Hugging Face Hub models using inspect-ai and lighteval on local hardware. Use for backend selection, local GPU evals, and choosing between vLLM / Transformers / accelerate. Not for HF Jobs orchestration, model-card PRs, .eval_results publication, or community-evals automation.",{"claudeCode":265},"SKILL.md frontmatter at skills/huggingface-community-evals/SKILL.md",[493,494,497,499,501,503],{"path":322,"priority":307},{"path":495,"priority":496},"examples/.env.example","low",{"path":498,"priority":496},"examples/USAGE_EXAMPLES.md",{"path":500,"priority":496},"scripts/inspect_eval_uv.py",{"path":502,"priority":496},"scripts/inspect_vllm_uv.py",{"path":504,"priority":496},"scripts/lighteval_vllm_uv.py",{"basePath":377,"description":506,"displayName":379,"installMethods":507,"rationale":508,"selectedPaths":509,"source":313,"sourceLanguage":17,"type":475},"Use this skill for Hugging Face Dataset Viewer API workflows that fetch subset/split metadata, paginate rows, search text, apply filters, download parquet URLs, and read size or statistics.\r",{"claudeCode":265},"SKILL.md frontmatter at skills/huggingface-datasets/SKILL.md",[510],{"path":322,"priority":307},{"basePath":393,"description":394,"displayName":395,"installMethods":512,"rationale":513,"selectedPaths":514,"source":313,"sourceLanguage":17,"type":475},{"claudeCode":265},"SKILL.md frontmatter at skills/huggingface-gradio/SKILL.md",[515,516],{"path":322,"priority":307},{"path":517,"priority":434},"examples.md",{"basePath":315,"description":519,"displayName":317,"installMethods":520,"rationale":521,"selectedPaths":522,"source":313,"sourceLanguage":17,"type":475},"Train or fine-tune language and vision models using TRL (Transformer Reinforcement Learning) or Unsloth with Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes guidance on the TRL Jobs package, UV scripts with PEP 723 format, dataset preparation and validation, hardware selection, cost estimation, Trackio monitoring, Hub authentication, model selection/leaderboards and model persistence. Use for tasks involving cloud GPU training, GGUF conversion, or when users mention training on Hugging Face Jobs without local GPU setup.",{"claudeCode":265},"SKILL.md frontmatter at skills/huggingface-llm-trainer/SKILL.md",[523,524,526,528,530,532,534,536,538,540,542,544,546,548,550,552,554,556,558],{"path":322,"priority":307},{"path":525,"priority":434},"references/gguf_conversion.md",{"path":527,"priority":434},"references/hardware_guide.md",{"path":529,"priority":434},"references/hub_saving.md",{"path":531,"priority":434},"references/local_training_macos.md",{"path":533,"priority":434},"references/reliability_principles.md",{"path":535,"priority":434},"references/trackio_guide.md",{"path":537,"priority":434},"references/training_methods.md",{"path":539,"priority":434},"references/training_patterns.md",{"path":541,"priority":434},"references/troubleshooting.md",{"path":543,"priority":434},"references/unsloth.md",{"path":545,"priority":496},"scripts/convert_to_gguf.py",{"path":547,"priority":496},"scripts/dataset_inspector.py",{"path":549,"priority":496},"scripts/estimate_cost.py",{"path":551,"priority":496},"scripts/hf_benchmarks.py",{"path":553,"priority":496},"scripts/train_dpo_example.py",{"path":555,"priority":496},"scripts/train_grpo_example.py",{"path":557,"priority":496},"scripts/train_sft_example.py",{"path":559,"priority":496},"scripts/unsloth_sft_example.py",{"basePath":324,"description":325,"displayName":326,"installMethods":561,"rationale":562,"selectedPaths":563,"source":313,"sourceLanguage":17,"type":475},{"claudeCode":265},"SKILL.md frontmatter at skills/huggingface-local-models/SKILL.md",[564,565,567,569],{"path":322,"priority":307},{"path":566,"priority":434},"references/hardware.md",{"path":568,"priority":434},"references/hub-discovery.md",{"path":570,"priority":434},"references/quantization.md",{"basePath":332,"description":333,"displayName":334,"installMethods":572,"rationale":573,"selectedPaths":574,"source":313,"sourceLanguage":17,"type":475},{"claudeCode":265},"SKILL.md frontmatter at skills/huggingface-paper-publisher/SKILL.md",[575,576,578,580,582,584,586,588],{"path":322,"priority":307},{"path":577,"priority":496},"examples/example_usage.md",{"path":579,"priority":434},"references/quick_reference.md",{"path":581,"priority":496},"scripts/paper_manager.py",{"path":583,"priority":496},"templates/arxiv.md",{"path":585,"priority":496},"templates/ml-report.md",{"path":587,"priority":496},"templates/modern.md",{"path":589,"priority":496},"templates/standard.md",{"basePath":340,"description":591,"displayName":342,"installMethods":592,"rationale":593,"selectedPaths":594,"source":313,"sourceLanguage":17,"type":475},"Look up and read Hugging Face paper pages in markdown, and use the papers API for structured metadata such as authors, linked models/datasets/spaces, Github repo and project page. Use when the user shares a Hugging Face paper page URL, an arXiv URL or ID, or asks to summarize, explain, or analyze an AI research paper.",{"claudeCode":265},"SKILL.md frontmatter at skills/huggingface-papers/SKILL.md",[595],{"path":322,"priority":307},{"basePath":385,"description":597,"displayName":387,"installMethods":598,"rationale":599,"selectedPaths":600,"source":313,"sourceLanguage":17,"type":475},"Use this skill when the user wants to build tool/scripts or achieve a task where using data from the Hugging Face API would help. This is especially useful when chaining or combining API calls or the task will be repeated/automated. This Skill creates a reusable script to fetch, enrich or process data.",{"claudeCode":265},"SKILL.md frontmatter at skills/huggingface-tool-builder/SKILL.md",[601,602,604,606,608,610,612,614],{"path":322,"priority":307},{"path":603,"priority":434},"references/baseline_hf_api.py",{"path":605,"priority":434},"references/baseline_hf_api.sh",{"path":607,"priority":434},"references/baseline_hf_api.tsx",{"path":609,"priority":434},"references/find_models_by_paper.sh",{"path":611,"priority":434},"references/hf_enrich_models.sh",{"path":613,"priority":434},"references/hf_model_card_frontmatter.sh",{"path":615,"priority":434},"references/hf_model_papers_auth.sh",{"basePath":369,"description":617,"displayName":371,"installMethods":618,"rationale":619,"selectedPaths":620,"source":313,"sourceLanguage":17,"type":475},"Track and visualize ML training experiments with Trackio. Use when logging metrics during training (Python API), firing alerts for training diagnostics, or retrieving/analyzing logged metrics (CLI). Supports real-time dashboard visualization, alerts with webhooks, HF Space syncing, and JSON output for automation.",{"claudeCode":265},"SKILL.md frontmatter at skills/huggingface-trackio/SKILL.md",[621,622,624,626],{"path":322,"priority":307},{"path":623,"priority":434},"references/alerts.md",{"path":625,"priority":434},"references/logging_metrics.md",{"path":627,"priority":434},"references/retrieving_metrics.md",{"basePath":409,"description":629,"displayName":411,"installMethods":630,"rationale":631,"selectedPaths":632,"source":313,"sourceLanguage":17,"type":475},"Trains and fine-tunes vision models for object detection (D-FINE, RT-DETR v2, DETR, YOLOS), image classification (timm models — MobileNetV3, MobileViT, ResNet, ViT/DINOv3 — plus any Transformers classifier), and SAM/SAM2 segmentation using Hugging Face Transformers on Hugging Face Jobs cloud GPUs. Covers COCO-format dataset preparation, Albumentations augmentation, mAP/mAR evaluation, accuracy metrics, SAM segmentation with bbox/point prompts, DiceCE loss, hardware selection, cost estimation, Trackio monitoring, and Hub persistence. Use when users mention training object detection, image classification, SAM, SAM2, segmentation, image matting, DETR, D-FINE, RT-DETR, ViT, timm, MobileNet, ResNet, bounding box models, or fine-tuning vision models on Hugging Face Jobs.",{"claudeCode":265},"SKILL.md frontmatter at skills/huggingface-vision-trainer/SKILL.md",[633,634,636,637,639,641,642,644,645,646,648,650],{"path":322,"priority":307},{"path":635,"priority":434},"references/finetune_sam2_trainer.md",{"path":529,"priority":434},{"path":638,"priority":434},"references/image_classification_training_notebook.md",{"path":640,"priority":434},"references/object_detection_training_notebook.md",{"path":533,"priority":434},{"path":643,"priority":434},"references/timm_trainer.md",{"path":547,"priority":496},{"path":549,"priority":496},{"path":647,"priority":496},"scripts/image_classification_training.py",{"path":649,"priority":496},"scripts/object_detection_training.py",{"path":651,"priority":496},"scripts/sam_segmentation_training.py",{"basePath":417,"description":653,"displayName":419,"installMethods":654,"rationale":655,"selectedPaths":656,"source":313,"sourceLanguage":17,"type":475},"Train or fine-tune sentence-transformers models across `SentenceTransformer` (bi-encoder; dense or static embedding model; for retrieval, similarity, clustering, classification, paraphrase mining, dedup, multimodal), `CrossEncoder` (reranker; pair scoring for two-stage retrieval / pair classification), and `SparseEncoder` (SPLADE, sparse embedding model; for learned-sparse retrieval). Covers loss selection, hard-negative mining, evaluators, distillation, LoRA, Matryoshka, and Hugging Face Hub publishing. Use for any sentence-transformers training task.",{"claudeCode":265},"SKILL.md frontmatter at skills/train-sentence-transformers/SKILL.md",[657,658,660,662,664,666,668,669,671,673,675,677,679,681,683,684,686,688,690,692,694,696,698,700,702,704,706,708],{"path":322,"priority":307},{"path":659,"priority":434},"references/base_model_selection.md",{"path":661,"priority":434},"references/dataset_formats.md",{"path":663,"priority":434},"references/evaluators_cross_encoder.md",{"path":665,"priority":434},"references/evaluators_sentence_transformer.md",{"path":667,"priority":434},"references/evaluators_sparse_encoder.md",{"path":527,"priority":434},{"path":670,"priority":434},"references/hf_jobs_execution.md",{"path":672,"priority":434},"references/losses_cross_encoder.md",{"path":674,"priority":434},"references/losses_sentence_transformer.md",{"path":676,"priority":434},"references/losses_sparse_encoder.md",{"path":678,"priority":434},"references/model_architectures.md",{"path":680,"priority":434},"references/prompts_and_instructions.md",{"path":682,"priority":434},"references/training_args.md",{"path":541,"priority":434},{"path":685,"priority":496},"scripts/mine_hard_negatives.py",{"path":687,"priority":496},"scripts/train_cross_encoder_distillation_example.py",{"path":689,"priority":496},"scripts/train_cross_encoder_example.py",{"path":691,"priority":496},"scripts/train_cross_encoder_listwise_example.py",{"path":693,"priority":496},"scripts/train_sentence_transformer_distillation_example.py",{"path":695,"priority":496},"scripts/train_sentence_transformer_example.py",{"path":697,"priority":496},"scripts/train_sentence_transformer_make_multilingual_example.py",{"path":699,"priority":496},"scripts/train_sentence_transformer_matryoshka_example.py",{"path":701,"priority":496},"scripts/train_sentence_transformer_multi_dataset_example.py",{"path":703,"priority":496},"scripts/train_sentence_transformer_static_embedding_example.py",{"path":705,"priority":496},"scripts/train_sentence_transformer_with_lora_example.py",{"path":707,"priority":496},"scripts/train_sparse_encoder_distillation_example.py",{"path":709,"priority":496},"scripts/train_sparse_encoder_example.py",{"basePath":401,"description":711,"displayName":403,"installMethods":712,"rationale":713,"selectedPaths":714,"source":313,"sourceLanguage":17,"type":475},"Use Transformers.js to run state-of-the-art machine learning models directly in JavaScript/TypeScript. Supports NLP (text classification, translation, summarization), computer vision (image classification, object detection), audio (speech recognition, audio classification), and multimodal tasks. Works in browsers and server-side runtimes (Node.js, Bun, Deno) with WebGPU/WASM using pre-trained models from Hugging Face Hub.",{"claudeCode":265},"SKILL.md frontmatter at skills/transformers-js/SKILL.md",[715,716,718,720,722,724,726,728],{"path":322,"priority":307},{"path":717,"priority":434},"references/CACHE.md",{"path":719,"priority":434},"references/CONFIGURATION.md",{"path":721,"priority":434},"references/EXAMPLES.md",{"path":723,"priority":434},"references/MODEL_ARCHITECTURES.md",{"path":725,"priority":434},"references/MODEL_REGISTRY.md",{"path":727,"priority":434},"references/PIPELINE_OPTIONS.md",{"path":729,"priority":434},"references/TEXT_GENERATION.md",{"sources":731},[732],"manual",{"closedIssues90d":243,"description":734,"forks":244,"homepage":735,"license":249,"openIssues90d":245,"pushedAt":246,"readmeSize":241,"stars":247,"topics":736},"Give your agents the power of the Hugging Face ecosystem","https://huggingface.co",[],{"classifiedAt":738,"discoverAt":739,"extractAt":740,"githubAt":740,"updatedAt":738},1778690772996,1778689536128,1778690770714,[223,226,224,222,225,227],{"evaluatedAt":253,"extractAt":289,"updatedAt":253},[],[745,763,783,803,834,853],{"_creationTime":746,"_id":747,"community":748,"display":749,"identity":751,"providers":752,"relations":759,"tags":760,"workflow":761},1778690773482.4844,"k1785s3263hzxs6ne1nsbzas5186m86v",{"reviewCount":8},{"description":370,"installMethods":750,"name":371,"sourceUrl":13},{"claudeCode":371},{"basePath":369,"githubOwner":222,"githubRepo":256,"locale":17,"slug":371,"type":257},{"evaluate":753,"extract":758},{"promptVersionExtension":215,"promptVersionScoring":216,"score":219,"tags":754,"targetMarket":228,"tier":229},[225,755,756,222,757,223],"experiment-tracking","monitoring","python",{"commitSha":279},{"parentExtensionId":260,"repoId":285},[223,755,222,225,756,757],{"evaluatedAt":762,"extractAt":289,"updatedAt":762},1778690988981,{"_creationTime":764,"_id":765,"community":766,"display":767,"identity":769,"providers":770,"relations":779,"tags":780,"workflow":781},1778690773482.4827,"k175sdyyg60kjnnbkm4029s70186ngbn",{"reviewCount":8},{"description":316,"installMethods":768,"name":317,"sourceUrl":13},{"claudeCode":317},{"basePath":315,"githubOwner":222,"githubRepo":256,"locale":17,"slug":317,"type":257},{"evaluate":771,"extract":778},{"promptVersionExtension":215,"promptVersionScoring":216,"score":219,"tags":772,"targetMarket":228,"tier":229},[773,774,775,222,776,777,225],"llm","training","fine-tuning","trl","gguf",{"commitSha":279},{"parentExtensionId":260,"repoId":285},[775,777,222,773,225,774,776],{"evaluatedAt":782,"extractAt":289,"updatedAt":782},1778690836703,{"_creationTime":784,"_id":785,"community":786,"display":787,"identity":790,"providers":791,"relations":799,"tags":800,"workflow":801},1778690773482.486,"k175g1spb5757qt4tnj9cktcn986mshy",{"reviewCount":8},{"description":263,"installMethods":788,"name":789,"sourceUrl":13},{"claudeCode":266},"Hugging Face Skills",{"basePath":268,"githubOwner":222,"githubRepo":256,"locale":17,"slug":256,"type":257},{"evaluate":792,"extract":797},{"promptVersionExtension":215,"promptVersionScoring":216,"score":793,"tags":794,"targetMarket":228,"tier":229},98,[222,795,796,226,227,774,223,757],"ai","ml",{"commitSha":279,"license":249,"plugin":798},{"mcpCount":8,"provider":283,"skillCount":281},{"repoId":285},[795,223,226,222,796,227,757,774],{"evaluatedAt":802,"extractAt":289,"updatedAt":802},1778691185872,{"_creationTime":804,"_id":805,"community":806,"display":807,"identity":812,"providers":817,"relations":825,"tags":829,"workflow":830},1778698425464.3115,"k17a9y822as9hqmk8ts9d8ck8d86m4a8",{"reviewCount":8},{"description":808,"installMethods":809,"name":810,"sourceUrl":811},"Upstash Context7 MCP-Server für die Abfrage aktueller Dokumentationen. Ruft versionsspezifische Dokumentationen und Codebeispiele direkt aus Quell-Repositories in den LLM-Kontext.",{"claudeCode":810},"context7-plugin","https://github.com/upstash/context7",{"basePath":813,"githubOwner":814,"githubRepo":815,"locale":816,"slug":815,"type":257},"plugins/claude/context7","upstash","context7","de",{"evaluate":818,"extract":824},{"promptVersionExtension":215,"promptVersionScoring":216,"score":819,"tags":820,"targetMarket":228,"tier":229},100,[821,224,822,823],"documentation","code-examples","mcp-server",{"commitSha":279},{"parentExtensionId":826,"repoId":827,"translatedFrom":828},"k17c6qmv4dnjycsp8aa4wyfbgh86n3jd","kd7955sg5wbf89gw527wdep66n86na9w","k17f8b1e3611rh6d9e6peh43b186m55k",[822,224,821,823],{"evaluatedAt":831,"extractAt":832,"updatedAt":833},1778698268645,1778698235845,1778698425464,{"_creationTime":835,"_id":836,"community":837,"display":838,"identity":841,"providers":842,"relations":849,"tags":850,"workflow":851},1778690773482.4834,"k179sm2kkyd7r7nz9jsx62jm9x86mw4a",{"reviewCount":8},{"description":341,"installMethods":839,"name":840,"sourceUrl":13},{"claudeCode":342},"Hugging Face Papers",{"basePath":340,"githubOwner":222,"githubRepo":256,"locale":17,"slug":342,"type":257},{"evaluate":843,"extract":848},{"promptVersionExtension":215,"promptVersionScoring":216,"score":819,"tags":844,"targetMarket":228,"tier":229},[222,845,846,795,277,847],"papers","arxiv","metadata",{"commitSha":279,"license":249},{"parentExtensionId":260,"repoId":285},[795,846,222,847,845,277],{"evaluatedAt":852,"extractAt":289,"updatedAt":852},1778690901306,{"_creationTime":854,"_id":855,"community":856,"display":857,"identity":859,"providers":860,"relations":867,"tags":868,"workflow":869},1778690773482.483,"k172w5kkdn7117xpqyyhcqsww186n17b",{"reviewCount":8},{"description":325,"installMethods":858,"name":326,"sourceUrl":13},{"claudeCode":326},{"basePath":324,"githubOwner":222,"githubRepo":256,"locale":17,"slug":326,"type":257},{"evaluate":861,"extract":866},{"promptVersionExtension":215,"promptVersionScoring":216,"score":219,"tags":862,"targetMarket":228,"tier":229},[773,863,864,777,222,865],"local-models","llama-cpp","ml-ops",{"commitSha":279},{"parentExtensionId":260,"repoId":285},[777,222,864,773,863,865],{"evaluatedAt":870,"extractAt":289,"updatedAt":870},1778690852474]