Fine-tuning corpora
Domain text and structured records collected with provenance.
Load the latest run with the datasets library and push it to a private Hub repo, versioned and ready for training or evaluation.
import os
from datasets import load_dataset
ds = load_dataset("json", data_files=os.environ["IMPORTIO_JSON_URL"], split="train") # NDJSON
ds.push_to_hub("your-org/retail-prices-2026", private=True)Any public page, rendered, through managed proxies
Rendering, proxy routing, captcha handling, extraction
Latest successful run, CSV or JSON
Extracted records pushed as a versioned dataset to the Hub.
Also connects via managed delivery.
Domain text and structured records collected with provenance.
Rebuild eval sets from today’s pages so models are tested on the live web.
Private repos with versions, dataset cards and access control.
pip install datasets.huggingface-cli login.push_to_hub.Yes. Managed Services build training and evaluation datasets to your specification, with schemas and provenance, and deliver them into your storage.
No. The latest-run CSV, JSON and Google Sheets endpoints return data your extractor already collected, so they don’t count toward your plan. Only the Live Query API runs an extraction per request.
As fresh as your schedule. Run the extractor hourly, daily or weekly and the endpoint always serves the latest successful run.
Your Managed Services team. They agree destination, format, schedule and schema with you, then build, run, monitor and QA the feed under an SLA.
Amazon S3, Google Cloud Storage, Azure Blob Storage, SFTP, Snowflake, BigQuery, API, email and Slack alerts. Aperture delivers into the same destinations.
Extracted pages embedded into a vector index for RAG.
Setup 15 minEndpointREST APILatest-run data into a DataFrame in three lines.
Setup 5 minS3 / SFTPManagedAuto Loader picks up every delivery into a Delta table.
Setup 15 minS3 / SFTPManagedEvery run delivered into your bucket, on schedule.
Setup 10 min