# Hugging Face Models Scraper - AI Model Intelligence (`thirdwatch/hugging-face-models-scraper`) Actor

Search public Hugging Face models and export downloads, likes, task, library, license, tags, files, gated status, hashes, timestamps, authors, and canonical model URLs. Built for research and data pipelines. No login, cookies, or API keys — clean JSON output and pay-per-result pricing.

- **URL**: https://apify.com/thirdwatch/hugging-face-models-scraper.md
- **Developed by:** [Thirdwatch](https://apify.com/thirdwatch) (community)
- **Categories:** AI, Developer tools
- **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.00 / 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?

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 Models Scraper

Search the public Hugging Face Hub through its JSON API and export AI model metadata as JSON, CSV, or Excel. Cursor pagination, task filtering, and deterministic sorting make it useful for repeatable model-market research without browser compute.

### What you get

- Model ID, author, canonical URL, task, library, license, tags, and repository hash
- Downloads, likes, created and modified timestamps, gated status, and public/private flag
- Up to 100 filenames plus the complete file count for packaging and format analysis
- Query provenance, cross-query deduplication, and cursor pagination in 256 MB

### Output fields

Common fields are `modelId`, `author`, `url`, `pipelineTag`, `library`, `license`, `downloads`, `likes`, `gated`, `private`, `sha`, `createdAt`, `lastModified`, `tags`, `files`, `filesCount`, `searchQuery`, and `source`.

### Example output

```json
{"modelId":"meta-llama/Llama-3.1-8B-Instruct","pipelineTag":"text-generation","library":"transformers","downloads":1000000,"likes":5000,"gated":"manual","url":"https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct"}
```

### Input parameters

| Parameter | Description |
|---|---|
| `queries` | Public Hub model search terms. |
| `pipelineTag` | Optional task filter such as text-generation or text-to-image. |
| `sort` | Downloads, likes, recently modified, or recently created. |
| `maxResultsPerQuery` | Maximum public models saved per query. |
| `maxResults` | Maximum unique public models saved across all queries. |

### Use cases

AI model discovery, open-source intelligence, license screening, model adoption tracking, inference-platform planning, competitor research, task coverage maps, model-format analysis, and scheduled ecosystem monitoring.

### Limitations

Search ranking and download counts are supplied by Hugging Face and can change. Gated metadata can be public even when weights require acceptance; this Actor never bypasses gating or downloads model weights. File lists are capped at 100 names per row while `filesCount` preserves the total.

### Compared to alternatives

Thirdwatch uses the public Hub API and cursor links, includes license and file intelligence, and charges $0.002 at the base tier versus $0.005 on the leading observed competitor. Start with the [Hugging Face Models Scraper](https://apify.com/thirdwatch/hugging-face-models-scraper), browse [all Thirdwatch Actors](https://apify.com/thirdwatch), or read the [Hugging Face model-data guide](https://thirdwatch.dev/actors/hugging-face-models-scraper).

### FAQ

**Does it download models?** No. It exports public Hub metadata and evidence URLs only.

**Are private models included?** No. Any response explicitly marked private is skipped.

Open the [input form](https://apify.com/thirdwatch/hugging-face-models-scraper?tab=input) or review [recent runs](https://apify.com/thirdwatch/hugging-face-models-scraper?tab=runs) after launch.

Last verified: 2026-07

# Actor input Schema

## `queries` (type: `array`):

Model names, capabilities, organizations, or keywords searched through the public Hugging Face Hub API.

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

Optional Hub pipeline tag such as text-generation, text-to-image, image-classification, or feature-extraction.

## `sort` (type: `string`):

Hub metadata field used to rank results.

## `maxResultsPerQuery` (type: `integer`):

Maximum unique public model records saved for each query.

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

Maximum unique public models saved across all queries.

## Actor input object example

```json
{
  "queries": [
    "llama"
  ],
  "pipelineTag": "",
  "sort": "downloads",
  "maxResultsPerQuery": 25,
  "maxResults": 100
}
```

# 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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("thirdwatch/hugging-face-models-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 = {}

# Run the Actor and wait for it to finish
run = client.actor("thirdwatch/hugging-face-models-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 '{}' |
apify call thirdwatch/hugging-face-models-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,thirdwatch/hugging-face-models-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/W6fP5g2U1HecceoAy/builds/2GCzSdJi3XHxB1Q6L/openapi.json