# Hugging Face Scraper Goat (`goat255/huggingface-scraper`) Actor Scrape the Hugging Face Hub without a login. Search or list AI models, datasets, and spaces, sorted by downloads, likes, trending, or recency, and optionally filtered by task, library, or author. Returns clean rows with downloads, likes, task, library, tags, file count, and dates. - **URL**: https://apify.com/goat255/huggingface-scraper.md - **Developed by:** [Goutam Soni](https://apify.com/goat255) (community) - **Categories:** Developer tools, Automation, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Hugging Face Scraper Search and list AI models, datasets and spaces from the Hugging Face Hub at scale, no login or API key. Sort by downloads, likes, trending, or recency, and filter by task, library, or author. Every row comes back in one clean, structured shape with downloads, likes, task, library, tags, file count and dates. ### What it does - **Search** - models, datasets or spaces matching your terms. - **Top listings** - leave the search empty to pull the top items by your chosen sort (for example the most-downloaded text-generation models). - **Filters** - narrow by task (e.g. `text-generation`), library (e.g. `transformers`), or author / organization (e.g. `google`). - **Direct lookup** - fetch specific Hub IDs. Common uses: AI/ML market and trend research, model discovery and monitoring, dataset sourcing, competitor tracking, and building an AI catalog. ### Input | Field | Type | Description | |---|---|---| | `resource` | string | `models`, `datasets`, or `spaces`. | | `searchQueries` | array | Terms to search. Empty = top listing by sort. | | `directIds` | array | Specific Hub IDs, e.g. `openai-community/gpt2`. | | `sort` | string | `downloads`, `likes`, `trending`, `lastModified`, `createdAt`. | | `filter` | string | Optional task or library filter. | | `author` | string | Optional author / organization. | | `maxItemsPerSource` | integer | Cap per query. Default 50, up to 1000. | | `proxyConfiguration` | object | Optional. Works without a proxy. | #### Example input ```json { "resource": "models", "searchQueries": ["llama", "whisper"], "sort": "downloads", "filter": "text-generation", "maxItemsPerSource": 100 } ```` ### Output Each item is one normalized model, dataset, or space. ```json { "resource": "models", "id": "openai-community/gpt2", "author": "openai-community", "name": "gpt2", "downloads": 14024247, "downloadsAllTime": null, "likes": 3355, "trendingScore": null, "task": "text-generation", "library": "transformers", "tags": ["transformers", "pytorch", "text-generation"], "gated": false, "private": false, "disabled": false, "fileCount": 26, "createdAt": "2022-03-02T23:29:04.000Z", "lastModified": "2024-02-19T10:57:45.000Z", "sha": "607a30d783dfa663caf39e06633721c8d4cfcd7e", "url": "https://huggingface.co/openai-community/gpt2", "scrapedAt": "2026-07-18T13:00:00.000Z" } ``` Fields that do not apply (for example `task` on a dataset) come back as `null`, so the shape is always the same. ### Notes - No login and no API key. Pick a resource, set your terms or a sort, and run. - Leave `searchQueries` empty and set `sort` to `trending` to track what is hot on the Hub right now. - `maxItemsPerSource` goes up to 1000 per query for large catalogs. **Found this useful?** [Leave a quick review](https://apify.com/goat255/huggingface-scraper/reviews). It takes a few seconds and it genuinely helps other people find the actor. # Actor input Schema ## `resource` (type: `string`): What to scrape from the Hub. ## `searchQueries` (type: `array`): Terms to search. Leave empty to get the top listing by the chosen sort (e.g. most-downloaded models). ## `directIds` (type: `array`): Specific Hub IDs to fetch, e.g. "openai-community/gpt2" or "meta-llama/Llama-3.2-1B". ## `sort` (type: `string`): Ordering for listings and searches. ## `filter` (type: `string`): Optional filter, e.g. a task like "text-generation" or a library like "transformers". ## `author` (type: `string`): Optional. Limit to one author or organization, e.g. "google" or "meta-llama". ## `maxItemsPerSource` (type: `integer`): Cap per search query or listing. ## `proxyConfiguration` (type: `object`): Optional. The Hub API is public and works without a proxy. ## Actor input object example ```json { "resource": "models", "searchQueries": [ "llama", "whisper" ], "directIds": [ "openai-community/gpt2" ], "sort": "downloads", "maxItemsPerSource": 50, "proxyConfiguration": { "useApifyProxy": false } } ``` # Actor output Schema ## `results` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "searchQueries": [], "directIds": [], "filter": "", "author": "", "proxyConfiguration": { "useApifyProxy": false } }; // Run the Actor and wait for it to finish const run = await client.actor("goat255/huggingface-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "searchQueries": [], "directIds": [], "filter": "", "author": "", "proxyConfiguration": { "useApifyProxy": False }, } # Run the Actor and wait for it to finish run = client.actor("goat255/huggingface-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "searchQueries": [], "directIds": [], "filter": "", "author": "", "proxyConfiguration": { "useApifyProxy": false } }' | apify call goat255/huggingface-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=goat255/huggingface-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Hugging Face Scraper Goat", "description": "Scrape the Hugging Face Hub without a login. Search or list AI models, datasets, and spaces, sorted by downloads, likes, trending, or recency, and optionally filtered by task, library, or author. Returns clean rows with downloads, likes, task, library, tags, file count, and dates.", "version": "0.1", "x-build-id": "zShYMWC5pdrlgUoJy" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/goat255~huggingface-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-goat255-huggingface-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/goat255~huggingface-scraper/runs": { "post": { "operationId": "runs-sync-goat255-huggingface-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/goat255~huggingface-scraper/run-sync": { "post": { "operationId": "run-sync-goat255-huggingface-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "resource": { "title": "Resource", "enum": [ "models", "datasets", "spaces" ], "type": "string", "description": "What to scrape from the Hub.", "default": "models" }, "searchQueries": { "title": "Search queries", "type": "array", "description": "Terms to search. Leave empty to get the top listing by the chosen sort (e.g. most-downloaded models).", "items": { "type": "string" } }, "directIds": { "title": "Direct IDs", "type": "array", "description": "Specific Hub IDs to fetch, e.g. \"openai-community/gpt2\" or \"meta-llama/Llama-3.2-1B\".", "items": { "type": "string" } }, "sort": { "title": "Sort by", "enum": [ "downloads", "likes", "trending", "lastModified", "createdAt" ], "type": "string", "description": "Ordering for listings and searches.", "default": "downloads" }, "filter": { "title": "Filter (task or library)", "type": "string", "description": "Optional filter, e.g. a task like \"text-generation\" or a library like \"transformers\"." }, "author": { "title": "Author / organization", "type": "string", "description": "Optional. Limit to one author or organization, e.g. \"google\" or \"meta-llama\"." }, "maxItemsPerSource": { "title": "Max results per query", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Cap per search query or listing.", "default": 50 }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Optional. The Hub API is public and works without a proxy." } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```