# 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/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — 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.

To improve our actors we collect anonymized usage telemetry (run stats and input patterns). No personal account data is collected.

# 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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# 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(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).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": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,goat255/huggingface-scraper"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/yA5ecjevC3m210eIr/builds/o61OEOY9ACVGTh34G/openapi.json