--- pretty_name: TheBlueScrubs-v1 (train) — fixed schema tags: - medical - healthcare - biology - text - pretraining - safety - classification - generation task_categories: - text-generation - text-classification language: - en license: apache-2.0 size_categories: - 10B Upstream details: The Blue Scrubs is a large, curated medical corpus designed for clinical LLMs, filtered via a logistic-regression screen and then Llama-3.1-70B evaluation; clinician and external checks reported high concordance. An oncology classifier adds cancer labels at scale. --- ## Why this fork? - **Fix:** Removes the `meta` column, unblocking usage with `datasets` streaming and dataframe backends. - **Scope:** Content is otherwise **unchanged** relative to upstream train split (same rows, fields, and values). - **Goal:** Provide a drop-in train split that **loads cleanly** in `datasets` without ad-hoc parsing workarounds. --- ## Data fields (train) | Field | Type | Description | |---|---|---| | `text` | string | Raw medical text extracted from SlimPajama/RedPajama sources. | --- ## Splits This repository publishes the **train** split only (11,080,331 documents). For methods, scope, and aggregate corpus statistics (including validation/test in the upstream project), see the original dataset card and paper. --- ## How to load ```python from datasets import load_dataset # streaming ds = load_dataset("openmed-community/TheBlueScrubs-v1-fixed", split="train", streaming=True) row = next(iter(ds)) row["text"] # non-streaming (if you have local storage/network bandwidth) ds = load_dataset("openmed-community/TheBlueScrubs-v1-fixed", split="train") ds.features