# Hugging Face Hub Models Scraper — Downloads, Trending, GGUF (`spotless_studios/huggingface-hub-scraper`) Actor

Extract AI models from the Hugging Face Hub API. Captures monthly downloads, total likes, trending velocity scores, pipeline task tags, licenses, parameter architectures, GGUF/Safetensors compatibility, cloud deployment providers, and arXiv paper IDs.

- **URL**: https://apify.com/spotless_studios/huggingface-hub-scraper.md
- **Developed by:** [Spotless Studios](https://apify.com/spotless_studios) (community)
- **Categories:** AI, Developer tools
- **Security:** Limited permissions
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.00 / 1,000 hugging face model extracteds

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Hugging Face Hub Models Scraper (Downloads, Trending, GGUF & Licenses)

Extract AI models from the **[Hugging Face Hub API](https://huggingface.co/models)**. Captures **monthly downloads**, **total likes**, **trending velocity scores**, **ML task / pipeline tags**, **open-source licenses**, **GGUF & Safetensors availability**, **base model lineage**, **cloud deployment providers**, and **arXiv paper IDs**.

Built for **AI infrastructure teams**, **ML researchers**, **GPU cloud providers**, and **LLM leaderboard & benchmark pipelines**.

***

### What Does This Scraper Extract?

| Field | Type | Description |
|---|---|---|
| `modelId` | `string` | Canonical `<author>/<model>` ID (`"meta-llama/Llama-3.3-70B-Instruct"`) |
| `author` | `string` | Organization or researcher handle |
| `modelName` | `string` | Model repository slug |
| `pipelineTag` | `string \| null` | Primary ML task (`text-generation`, `image-text-to-text`, `text-to-image`) |
| `libraryName` | `string \| null` | ML framework (`transformers`, `diffusers`, `vllm`, `gguf`) |
| `downloads` | `number` | Monthly downloads on Hugging Face |
| `likes` | `number` | Community likes / stars |
| `trendingScore` | `number` | Current Hugging Face trending velocity score |
| `license` | `string \| null` | Open-source or custom license (`apache-2.0`, `mit`, `llama3.3`) |
| `isGated` | `boolean` | Whether access requires gated approval |
| `hasSafetensors` | `boolean` | Whether `.safetensors` weights are included |
| `hasGguf` | `boolean` | Whether quantized `.gguf` weights are included |
| `arxivIds` | `string[]` | Linked arXiv research paper IDs (`["2407.21783"]`) |
| `baseModels` | `string[]` | Upstream base models for fine-tunes / merges / quantizations |
| `deployTargets` | `string[]` | Supported cloud deployment targets (`["azure", "sagemaker"]`) |
| `fileCount` | `number` | Number of files in the model repository |
| `modelUrl` | `string` | Direct Hugging Face model card URL |
| `scrapedAt` | `string` | ISO-8601 extraction timestamp |

***

### Input Example

```json
{
  "searchQuery": "qwen",
  "pipelineTag": "text-generation",
  "sortBy": "downloads",
  "minDownloads": 10000,
  "minLikes": 50,
  "excludeGated": true,
  "maxResults": 50
}
```

***

### More from Spotless Studios

**[All actors on Apify](https://apify.com/spotless_studios)** · Support: spotless.studios.info@gmail.com

| Actor | Best for |
|-------|----------|
| [SLED Government Bids](https://apify.com/spotless_studios/sled-procurement-scraper) | Daily US gov RFP / bid alerts |
| [Webflow Experts](https://apify.com/spotless_studios/webflow-experts-scraper) | Webflow agency & freelancer leads |
| [Stripe Partners](https://apify.com/spotless_studios/stripe-partners-scraper) | Stripe implementation partner lists |
| [UK Planning Applications](https://apify.com/spotless_studios/uk-planning-applications-scraper) | UK planning leads + agent contacts |
| [Product Hunt](https://apify.com/spotless_studios/product-hunt-scraper) | Every PH launch + makers / websites |
| [Duunitori Jobs](https://apify.com/spotless_studios/duunitori-jobs-scraper) | Finland job listings |
| [Clutch Agencies](https://apify.com/spotless_studios/clutch-agencies-scraper) | Clutch agency prospecting |
| [Skool Communities](https://apify.com/spotless_studios/skool-communities-scraper) | Skool community & creator leads |

# Actor input Schema

## `searchQuery` (type: `string`):

Model search keyword or author (e.g. "llama", "qwen", "deepseek", "whisper", "flux", "embedding"). Leave empty for top models.

## `pipelineTag` (type: `string`):

Filter by ML task (e.g. "text-generation", "image-text-to-text", "text-to-image", "automatic-speech-recognition", "feature-extraction").

## `sortBy` (type: `string`):

How to sort models on Hugging Face.

## `minDownloads` (type: `integer`):

Only keep models with at least this many downloads (0 = no minimum).

## `minLikes` (type: `integer`):

Only keep models with at least this many likes (0 = no minimum).

## `excludeGated` (type: `boolean`):

When enabled, only return open, ungated models.

## `includeKeywords` (type: `array`):

Keep items whose text fields contain these words. /regex/ supported.

## `excludeKeywords` (type: `array`):

Drop items containing any of these words or /regex/.

## `keywordMatch` (type: `string`):

Require any or all include keywords.

## `onlyNewItems` (type: `boolean`):

Remember items from previous runs and save only ones not seen before.

## `stateKey` (type: `string`):

Separate memory per saved search.

## `maxResults` (type: `integer`):

Stop after saving this many items.

## `outputPreset` (type: `string`):

Quickly choose how much data to save per record: full record, lean summary, or contacts & links only.

## `outputFields` (type: `array`):

Save only these fields, in this order. Supports nested dot-paths. Empty keeps all fields from the selected preset.

## `excludeFields` (type: `array`):

Remove specific fields from each saved record to keep datasets compact.

## `includeEmptyFields` (type: `boolean`):

When turned off, strips null, empty strings, empty arrays, and empty objects from every saved record.

## `requiredFields` (type: `array`):

Only save (and only pay for) records where every listed field has a non-empty value.

## `maxConcurrency` (type: `integer`):

Requests fetched in parallel.

## `maxRequestRetries` (type: `integer`):

Retries per request.

## `requestTimeoutSecs` (type: `integer`):

Timeout per request.

## `proxyConfiguration` (type: `object`):

Optional; direct connection is tried first.

## `proxyEscalation` (type: `boolean`):

If the site blocks the run, automatically step up from direct to Apify datacenter, then residential proxy.

## Actor input object example

```json
{
  "searchQuery": "llama",
  "pipelineTag": "",
  "sortBy": "downloads",
  "minDownloads": 0,
  "minLikes": 0,
  "excludeGated": false,
  "keywordMatch": "any",
  "onlyNewItems": false,
  "stateKey": "default",
  "maxResults": 25,
  "outputPreset": "full",
  "includeEmptyFields": true,
  "maxConcurrency": 6,
  "maxRequestRetries": 4,
  "requestTimeoutSecs": 45,
  "proxyConfiguration": {
    "useApifyProxy": false
  },
  "proxyEscalation": true
}
```

# Actor output Schema

## `items` (type: `string`):

Extract AI models from the Hugging Face Hub API. Captures monthly downloads, total likes, trending velocity scores, pipeline task tags, licenses, parameter architectures, GGUF/Safetensors compatibility, cloud deployment providers, and arXiv paper IDs.

# 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 = {
    "searchQuery": "llama",
    "maxResults": 25,
    "proxyConfiguration": {
        "useApifyProxy": false
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("spotless_studios/huggingface-hub-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 = {
    "searchQuery": "llama",
    "maxResults": 25,
    "proxyConfiguration": { "useApifyProxy": False },
}

# Run the Actor and wait for it to finish
run = client.actor("spotless_studios/huggingface-hub-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 '{
  "searchQuery": "llama",
  "maxResults": 25,
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}' |
apify call spotless_studios/huggingface-hub-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,spotless_studios/huggingface-hub-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/Twhh4hfcLi2cnbbHV/builds/aOhGccCRBRyQ50ozD/openapi.json