Hugging Face Scraper 🤗

AI model intelligence from the open Hugging Face Hub API — trending & most-downloaded models, datasets and spaces, by task, author and library. No API key, no login.

Track the AI landscape with clean, structured data straight from the Hugging Face Hub API: trending and most-downloaded models, datasets and spaces — filterable by task (text-generation, text-to-image, ASR…), author/org (Meta, Mistral, Google…) and library. Perfect for AI-trend monitoring, competitive intelligence on model labs, dataset discovery and building model catalogs.

Uses the open Hugging Face Hub API — public data, no key required.

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What you can do with it

• 🔥 Track trending models — what's rising on the Hub right now, by task.
• 🏢 Watch an AI lab — everything mistralai, meta-llama or google ships, by downloads.
• 📚 Discover datasets — find training data by popularity, task or tag.
• 🚀 Monitor Spaces — the most-liked live demos and apps.
• 📊 Build a model catalog — downloads, likes, tags and update dates for a whole task area.

Features

• ✅ No API key — open Hugging Face Hub endpoints, works out of the box.
• ✅ Models, datasets & spaces — one Actor, three resource types.
• ✅ Smart sorts — trending, downloads, likes, newest, recently updated.
• ✅ Filters — search, author/org, task/pipeline, library, tag.
• ✅ Scales — cursor-paginated, 100 items per page.

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Input

Field	Description
Resource	models / datasets / spaces.
Sort by	trending / downloads / likes / newest / recently updated.
Search	Free-text name search.
Author / organization	e.g. mistralai, meta-llama, google.
Task	Models only, e.g. text-generation, text-to-image.
Library / Tag	Extra model/library/tag filters.
Max results	Result cap.

Example — trending text-generation models

{
  "resource": "models",
  "sort": "trending",
  "task": "text-generation",
  "maxResults": 100
}

Example — everything Mistral ships, by downloads

{
  "resource": "models",
  "sort": "downloads",
  "author": "mistralai",
  "maxResults": 200
}

Output

One row per item:

{
  "type": "model",
  "id": "mistralai/Mistral-7B-Instruct-v0.3",
  "url": "https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3",
  "author": "mistralai",
  "downloads": 5438667,
  "likes": 2714,
  "trending_score": 12,
  "task": "text-generation",
  "library": "transformers",
  "tags": ["transformers", "safetensors", "mistral", "text-generation"],
  "last_modified": "2024-08-21T10:00:00.000Z"
}

Datasets and spaces carry the same core fields; spaces also include sdk (gradio/streamlit/docker), datasets include a short description.

Run it on a schedule

Schedule the Actor to snapshot trending models or a lab's releases over time, and connect a Google Sheets / Slack / webhook integration to get alerted when new models drop or downloads spike.

Notes & limitations

• Uses the open Hugging Face Hub API — no key needed (an optional token raises rate limits).
• Counts are point-in-time snapshots at run time.
• Public repository metadata (non-personal).
• Data source: Hugging Face Hub.

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Keywords

Hugging Face, huggingface, HF Hub, AI models, machine learning models, LLM, model scraper, Hugging Face API, model downloads, trending models, AI datasets, ML datasets, Hugging Face spaces, model catalog, AI trends, transformers, text-generation, model intelligence, ML data, AI research.