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Hugging Face

Поиск моделей, датасетов, Spaces и научных статей на Hugging Face Hub

Инструменты разработчикаавтор: Hugging Face · добавлен каталогомБесплатно✓ Проверен модератором
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Описание

Официальный сервер Hugging Face: ассистент ищет открытые модели, датасеты и демо-приложения (Spaces), смотрит их описания и файлы, находит научные статьи и то, что сейчас в тренде. Инструменты: - hub_repo_search — поиск по моделям, датасетам и Spaces; - hub_repo_details — подробности о репозитории: описание, структура датасета, файлы; - hf_fs — файлы репозиториев, статьи, трендовые модели, документация Hub; - hf_whoami — показывает, под каким аккаунтом идёт работа. Кому полезен: ML-инженерам, исследователям и разработчикам, которые подбирают модель или датасет под задачу. Примеры вопросов: — «Найди открытые модели для распознавания русской речи и сравни их по размеру» — «Какие датасеты есть для классификации отзывов на русском языке?» Публичные данные доступны без входа; с аккаунтом Hugging Face доступно больше.

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Инструменты · 4

из ответа tools/list

Hugging Face Hub: Find, use and view models, datasets, spaces, buckets, papers, documentation and collections. Get daily papers reports, and browse trending content.

hf_fs

When to use: Hugging Face Hub models, datasets, Spaces, collections, papers, daily papers, today's trending models, current paper leaderboard, docs, and repository files. Examples: {"operations":[{"cmd":"ls","args":["hf://models/trending","--limit","10"]}]} {"operations":[{"cmd":"ls","args":["hf://papers/trending"]}]} {"operations":[{"cmd":"ls","args":["hf://papers/daily/latest"]}]} {"operations":[{"cmd":"cat","args":["hf://papers/2501.00001/paper.md"]}]} Use hf_fs for Hugging Face Hub filesystem operations. Call it with operations, an array of {cmd, args} items; multiple operations may be submitted together. Usage: {"operations":[{"cmd":"ls","args":["hf://models/org/repo"]}]} Grammar; each string below is one args array item: ls URI [--recursive] [--glob GLOB] [--type TYPE] [--sort SORT] [--limit N] cat URI [--offset N] [--max-bytes N] attach URI [--max-bytes N] stat URI find URI [--name GLOB] [--path GLOB] [--type TYPE] [--limit N] search URI [QUERY] [--type TYPE] [--sort SORT] [--tag TAG] [--kind mcp] [--limit N] COMMAND = ls|cat|attach|stat|find|search. TYPE = file|dir|repo|bucket|collection|paper|link. SORT = createdAt|downloads|likes|lastModified|likes30d|trendingScore|mainSize|id|trending|upvotes. URI is a canonical hf:// URI. QUERY and GLOB are each one string. Use search for resource discovery, not repository-content search; ls for a known directory, find for recursive file discovery by name/path (not file contents), stat for filesystem metadata or an uncertain target type, cat for text contents, and attach for a complete JPEG, PNG, or WebP image. When the request gives an exact text-file URI, use cat directly; do not add ls or stat first. stat does not read the contents of JSON, Markdown, or other text files. Search scopes: hf://models[/OWNER], hf://datasets[/OWNER], hf://spaces[/OWNER], hf://collections[/OWNER], hf://papers, and hf://docs[/...]. Repository and repository-file scopes are not supported: search a resource root or owner scope to discover resources; use find for file discovery within a repository or cat for a known text file. Paper and documentation search require QUERY. --tag (repeatable) and --kind are supported only on exactly hf://spaces, not owner scopes or other roots. The only valid --kind value is mcp, which selects MCP Spaces. Use ls hf://models/trending, hf://datasets/trending, hf://spaces/trending, or hf://papers/trending for trending listings. hf://papers/ID is a paper directory, not paper text. Use cat hf://papers/ID/paper.md for paper text and cat hf://papers/ID/metadata.json for metadata. No preliminary listing is needed for these known paths. Use ls hf://papers/ID to discover other resources. Omit --limit, --sort, and --type unless the request requires them. Limits and path-specific behavior are documented at hf://README.md. Issue one hf_fs call.

hf_fs(operations: array)

Hugging Face User Info

hf_whoami

Inspect the current Hugging Face authentication context, including the account, visible organization memberships, and credential access details. Read-only and never returns credential values.

hf_whoami()

Hub Repository Details

hub_repo_details

Get details for one or more Hugging Face repos (model, dataset, or space). Auto-detects type unless specified. For datasets, use operations: overview, dataset_structure, dataset_preview. Use dataset_structure first to discover configs, splits, sizes, and schema. Use dataset_preview only when config and split are known, unless the dataset has a single config/split.

hub_repo_details(limit?: integer, split?: string, config?: string, offset?: integer, repo_ids: array, repo_type?: string, operations?: array)

Repo Search

hub_repo_search

Search Hugging Face repositories with a shared query interface. You can target models, datasets, spaces, or aggregate across multiple repo types in one call. Include links to repositories in your response.

hub_repo_search(sort?: string, limit?: number, query?: string, author?: string, filters?: array, repo_types?: array)

Вопросы, новые серверы, обсуждение MCP

t.me/rusmcp · t.me/RusMcp_bot