Hugging Face Models, Datasets & Spaces Scraper
Pricing
from $6.80 / 1,000 results
Hugging Face Models, Datasets & Spaces Scraper
Scrape Hugging Face Hub models, datasets and spaces with downloads, all-time downloads, likes, trending score, task, library, license, author, base model and dates. Track trending AI models and prolific authors. Export to JSON, CSV or Excel.
Pricing
from $6.80 / 1,000 results
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Scrapers Lat
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2 days ago
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Track trending AI models, datasets and spaces from the Hugging Face Hub with downloads, likes, trending score, task, library, license and author. Filter by keyword or task and export clean structured data for research, sourcing and lead generation.
| Downloads & likes plus trending score | Task, library & license per model | JSON / CSV / Excel output formats |
What you get
Each record is one model, dataset or space, ready for a dashboard, a market map or a spreadsheet:
- id and url: the full identifier and a direct link
- modelName and author: the item name and the author or organization behind it
- pipelineTag: the task, for example
text-generation,text-to-imageorautomatic-speech-recognition - library: the framework or SDK, for example
transformers,diffusersorgradio - downloads: downloads over the last 30 days
- downloadsAllTime: cumulative downloads since publication
- likes: community likes
- trendingScore: how much momentum the item has right now
- license: the declared license, for example
apache-2.0,mitorllama3.1 - baseModel: the parent model a fine-tune is derived from, when available
- gated: whether access is gated
- createdAt and lastModified: publication and last update dates
- tags: the full tag list (languages, tasks, datasets, arXiv links and more)
- observedAt: freshness
Who is it for
| Use case | Who benefits |
|---|---|
| AI market research | Analysts tracking which models and tasks are gaining traction |
| Model discovery | Engineers finding the best model for a task, ranked by downloads and likes |
| Lead generation | Teams identifying prolific authors and organizations in the AI space |
| Trend monitoring | Builders watching trending score to catch fast-rising models early |
How to use it
- Choose what to scrape: models, datasets or spaces.
- Optionally add a search keyword (for example
llama,whisper,stable-diffusion) and, for models, a task / pipeline tag. - Pick a sort (downloads, likes, trending or recently modified), set Max Items and run. Export as JSON, CSV or Excel, or pull it through the Apify API.
Frequently Asked Questions
What is the difference between downloads and downloadsAllTime?
downloads counts downloads over the last 30 days, so it reflects current usage. downloadsAllTime is the cumulative total since the item was published.
Can I get only one task, like text-to-image?
Yes. For models, set the task / pipeline tag (for example text-to-image or text-generation) to keep only models for that task.
What does trending score mean? It is a momentum signal that surfaces items gaining attention right now. Sort by trending to see what is rising fastest.
How fresh is the data? Downloads, likes and trending score are read live at run time, so each record reflects the item at the moment of the run (see observedAt).
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This actor is built and maintained by scrapers.lat, where we publish scrapers for public platforms: finance, news, real estate, jobs, e-commerce and government data. Browse the full catalog or ask us for a custom scraper at scrapers.lat.
This actor is an independent tool and has no affiliation with Hugging Face. It only accesses publicly available catalog data. Use the results in accordance with the source's terms.
