HuggingFace Model Scraper - AI/ML Model Data

Pricing

Rating

Developer

Actor stats

Categories

Share

Extract comprehensive AI/ML model metadata from the HuggingFace Hub. The HuggingFace Hub hosts over 1 million public models and is the central repository for the AI/ML community. This actor queries the public HuggingFace API to retrieve model names, task types, download counts, popularity metrics, licenses, libraries, and model card excerpts.

What You Can Do

• Browse top models sorted by total downloads, likes, trending score, or recently modified
• Filter by task type (text-generation, image-classification, sentence-similarity, and 25+ other pipeline tags)
• Filter by ML library (transformers, diffusers, sentence-transformers, GGUF, ONNX, and more)
• Filter by author/organization (meta-llama, google, microsoft, BAAI, Qwen, etc.)
• Search by keyword across model names and descriptions
• Extract model card excerpts — first 500 characters of each model's README
• Get spaces usage — count of HuggingFace Spaces using each model
• Retrieve dataset provenance — datasets referenced in model card metadata

Use Cases

• AI market intelligence — track which models are gaining downloads and likes
• VC and investment research — monitor model ecosystem trends by organization
• Enterprise model evaluation — shortlist foundation models by task type, license, and popularity
• Competitive analysis — compare model adoption across ML libraries and providers
• Dataset discovery — find which training datasets are most commonly used

Input Parameters

Output Fields

Each record contains:

Example Output

{
"model_id":"sentence-transformers/all-MiniLM-L6-v2",
"model_name":"all-MiniLM-L6-v2",
"pipeline_tag":"sentence-similarity",
"downloads_total":262278076,
"downloads_30d":null,
"likes":4833,
"library":"sentence-transformers",
"author":"sentence-transformers",
"tags":["sentence-transformers","pytorch","onnx","safetensors","bert","en"],
"license":"apache-2.0",
"model_size_params":null,
"last_modified":"2025-03-06T13:37:44.000Z",
"readme_excerpt":"# all-MiniLM-L6-v2\nThis is a sentence-transformers model...",
"spaces_count":100,
"datasets_used":["s2orc","ms_marco","gooaq","natural_questions"]
}

Technical Notes

• No authentication required — uses the public HuggingFace Hub API
• No proxy required — the API is publicly accessible without IP restrictions
• Rate limits — generous unauthenticated limits; a courtesy 100ms delay is applied between detail fetches
• Pagination — handles cursor-based pagination automatically, allowing retrieval of any number of models
• Two-pass enrichment — basic metadata is retrieved from the list endpoint; detailed fields (readme_excerpt, spaces_count, datasets_used) are fetched from the model detail endpoint

Data Source

HuggingFace Hub API — https://huggingface.co/api/models