# Hugging Face Trending Models, Datasets & AI Papers Radar (`authoritative_glen/huggingface-trending-models-radar`) Actor

Extract trending AI models, top datasets, daily research papers, author metrics, download velocity, and Hugging Face tags without API keys. MCP ready.

- **URL**: https://apify.com/authoritative_glen/huggingface-trending-models-radar.md
- **Developed by:** [Rahmad Rizki](https://apify.com/authoritative_glen) (community)
- **Categories:** AI, Developer tools, Business
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

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

## 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 Trending Models, Datasets & AI Papers Radar

Extract real-time trending AI models, high-velocity datasets, daily research papers, download metrics, and licensing metadata directly from Hugging Face without requiring API tokens or authentication keys.

Built natively for **AI Agents (Model Context Protocol / MCP)**, machine learning researchers, tech venture scouts, developers, and AI content curators.

***

### 🚀 Key Capabilities

- **🔥 Trending AI Models:** Monitor breakout open-source models across Transformers, LLMs, Vision, Audio, Multimodal, and Diffusion.
- **📦 Datasets Discovery:** Uncover trending pre-training corpora, instruction-tuning datasets, and evaluation benchmarks.
- **📄 Daily AI Research Papers:** Track breakthrough papers submitted to ArXiv with community upvotes and abstracts.
- **📊 Real-time Velocity & Engagement:** Capture live `trendingScore`, total `likes`, monthly `downloads`, and commit timestamps.
- **🏷️ Deep Tag & License Extraction:** Identify model architectures (`safetensors`, `endpoints_compatible`, `8-bit`, `fp8`) and explicit software licenses (`mit`, `apache-2.0`, `llama3`).
- **⚡ Zero Authentication Required:** Uses public high-throughput endpoints with zero rate-limit hurdles or login barriers.
- **🤖 MCP & AI Agent Native:** Structured JSON schema ready for instant ingestion into Claude Desktop, Cursor, ChatGPT, and LangChain pipelines.

***

### 💼 Ideal Use Cases

1. **AI Market Intelligence & VC Scouting:** Track breakout open-weight releases before they go viral on X or Hacker News.
2. **AI Agent Tooling (MCP):** Connect your autonomous AI coding agents to dynamically query state-of-the-art models for specific tasks (e.g. `image-text-to-text`, `text-generation`).
3. **Daily AI Newsletters & Curators:** Automatically compile daily or weekly roundups of top models and research papers.
4. **License & Compliance Auditing:** Monitor model licensing types (`mit`, `apache-2.0`, `commercial-friendly`) for enterprise adoption.

***

### 📥 Input Parameters

| Parameter | Type | Default | Description |
|---|---|---|---|
| `resourceType` | String | `"models"` | What to extract: `models`, `datasets`, or `papers`. |
| `sortBy` | String | `"trendingScore"` | Sort criterion: `trendingScore`, `likes`, `downloads`, `createdAt`, `lastModified`. |
| `searchQuery` | String | `""` | Optional keyword filter (e.g. `deepseek`, `llama`, `flux`, `whisper`). |
| `authorFilter` | String | `""` | Filter by organization/author (e.g. `deepseek-ai`, `meta-llama`, `google`). |
| `taskFilter` | String | `""` | Filter models by pipeline task (e.g. `text-generation`, `image-text-to-text`). |
| `maxResults` | Integer | `30` | Number of items to extract (1 to 200). |

***

### 📤 Output Dataset Schema

Each item pushed to your Apify dataset contains comprehensive metadata:

| Field | Type | Description |
|---|---|---|
| `id` | String | Unique repo slug (e.g. `deepseek-ai/DeepSeek-V4.1-Flash`) |
| `resourceType` | String | Type: `model`, `dataset`, or `paper` |
| `title` | String | Title or repository ID |
| `author` | String | Organization or creator username |
| `likes` | Integer | Community upvotes count |
| `trendingScore` | Integer | Hugging Face trending velocity score |
| `downloads` | Integer | Monthly download count |
| `pipelineTag` | String | Machine learning task tag |
| `license` | String | Model/dataset software license |
| `tags` | Array | Full list of Hugging Face tags |
| `tagsString` | String | Comma-separated tag string for spreadsheets |
| `createdAt` | String | ISO 8601 creation date |
| `lastModified` | String | ISO 8601 update date |
| `url` | String | Canonical link to Hugging Face page |
| `summary` | String | Descriptive summary or abstract snippet |

***

### 📋 Sample JSON Output

```json
[
  {
    "id": "deepseek-ai/DeepSeek-V4.1-Flash-1017",
    "resourceType": "model",
    "title": "deepseek-ai/DeepSeek-V4.1-Flash-1017",
    "author": "deepseek-ai",
    "likes": 3581,
    "trendingScore": 889,
    "downloads": 116770,
    "pipelineTag": "image-text-to-text",
    "libraryName": "transformers",
    "license": "mit",
    "tags": [
      "transformers",
      "safetensors",
      "deepseek_v41",
      "text-generation",
      "image-text-to-text",
      "license:mit"
    ],
    "tagsString": "transformers, safetensors, deepseek_v41, text-generation, image-text-to-text, license:mit",
    "createdAt": "2026-10-17T02:40:38.000Z",
    "lastModified": "2026-10-28T18:12:00.000Z",
    "private": false,
    "url": "https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash-1017",
    "summary": "Hugging Face AI Model deepseek-ai/DeepSeek-V4.1-Flash-1017 (image-text-to-text) with 3581 likes and 116770 downloads."
  }
]
```

***

### 💰 Pricing (Pay-Per-Event)

- **Actor Start:** $0.00008 per run
- **Per Result Item:** $0.0034 per extracted item ($3.40 / 1,000 items)
- **Zero Hidden Infrastructure Charges:** Platform usage compute fees are disabled for clean and transparent pricing.

# Actor input Schema

## `resourceType` (type: `string`):

Choose which Hugging Face resource to extract: AI Models, Datasets, or Daily Research Papers.

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

Sort order for models and datasets (ignored for papers).

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

Optional keyword query (e.g. 'deepseek', 'llama-3', 'flux', 'ocr', 'voice').

## `authorFilter` (type: `string`):

Filter by author or organization handle (e.g. 'meta-llama', 'deepseek-ai', 'google', 'mistralai').

## `taskFilter` (type: `string`):

Filter models by task (e.g. 'text-generation', 'image-text-to-text', 'text-to-image', 'automatic-speech-recognition').

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

Number of items to extract (1 to 200).

## Actor input object example

```json
{
  "resourceType": "models",
  "sortBy": "trendingScore",
  "searchQuery": "",
  "authorFilter": "",
  "taskFilter": "",
  "maxResults": 30
}
```

# 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("authoritative_glen/huggingface-trending-models-radar").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("authoritative_glen/huggingface-trending-models-radar").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 authoritative_glen/huggingface-trending-models-radar --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,authoritative_glen/huggingface-trending-models-radar"
        }
    }
}
```

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/3i9Y1YlRBAgvfM16K/builds/EGNGhcDxzuscFJMKd/openapi.json