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$4.00 / 1,000 rows

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Hugging Face Models & Datasets List to CSV (Model Scraper)

Try for free

Pricing

$4.00 / 1,000 rows

Rating

0.0

(0)

Developer

Francesco Correnti

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Total users

Monthly active users

6 days ago

Last modified

Hugging Face Models & Datasets List to CSV (Hugging Face Model Scraper)

Hugging Face model scraper: export a hugging face models list csv (or datasets) with one flat row per repo. Uses the public Hugging Face Hub API, no API key. Filter by task and license, sort by downloads, likes, last modified or trending. Rows include card-completeness flags (README, license, dataset link, model-index evals). $0.004 per row.

Input

{ "kind": "model", "task": "text-classification", "license": "mit", "sort": "downloads", "maxItems": 100 }

Field	Default	Meaning
`kind`	model	`model` or `dataset`
`task`	empty	Models: `pipeline_tag`. Datasets: `task_categories`. Empty = no filter
`license`	empty	License id, e.g. `mit`. Empty = no filter
`sort`	downloads	`downloads`, `likes`, `lastModified`, `trending` (descending)
`maxItems`	50	1 to 10000

Output

One row per item, keys in this order: id, author, downloads, likes, license, tags, pipeline_tag, lastModified, has_readme, has_license, has_dataset_link, has_model_index_eval. tags is joined with ; so the CSV stays flat. Missing numbers are 0, missing text is "", never null. Export as CSV from the dataset tab.

Sample row:

Field	Example
`id`	BAAI/bge-small-en-v1.5
`author`	BAAI
`downloads`	59413346
`likes`	643
`license`	mit
`tags`	sentence-transformers;pytorch;onnx;safetensors;bert;feature-...
`pipeline_tag`	feature-extraction
`lastModified`	2024-02-22T03:36:23.000Z
`has_readme`	true
`has_license`	true
`has_dataset_link`	false
`has_model_index_eval`	true

Pricing

Pay per event: row = $0.004 per row pushed. No other events. The run stops cleanly when your max-charge limit is reached.

Limits: public Hugging Face API only, no private or gated repos, API rate limits apply (429/5xx retried up to 5 times with backoff, 30 s timeout), maxItems capped at 10000.

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