From 91e335559f1f0e2d48cab53951a8de4eabc7c1e3 Mon Sep 17 00:00:00 2001 From: Philippe Laval Date: Wed, 24 Jun 2026 11:39:34 +0200 Subject: [PATCH] Update dataset source from 'imdb' to 'stanfordnlp/imdb' --- phases/00-setup-and-tooling/09-data-management/docs/en.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/phases/00-setup-and-tooling/09-data-management/docs/en.md b/phases/00-setup-and-tooling/09-data-management/docs/en.md index 583d3ee452..2f2dedb72f 100644 --- a/phases/00-setup-and-tooling/09-data-management/docs/en.md +++ b/phases/00-setup-and-tooling/09-data-management/docs/en.md @@ -45,7 +45,7 @@ pip install datasets huggingface_hub ```python from datasets import load_dataset -dataset = load_dataset("imdb") +dataset = load_dataset("stanfordnlp/imdb") print(dataset) print(dataset["train"][0]) ``` @@ -72,7 +72,7 @@ Streaming gives you an `IterableDataset`. You process rows as they arrive. Memor The `datasets` library uses Apache Arrow under the hood. You can convert to other formats depending on what your pipeline needs. ```python -dataset = load_dataset("imdb", split="train") +dataset = load_dataset("stanfordnlp/imdb", split="train") dataset.to_csv("imdb_train.csv") dataset.to_json("imdb_train.json") @@ -101,7 +101,7 @@ Every ML project needs three splits: Some datasets come pre-split. When they don't, split them yourself: ```python -dataset = load_dataset("imdb", split="train") +dataset = load_dataset("stanfordnlp/imdb", split="train") split = dataset.train_test_split(test_size=0.2, seed=42) train_val = split["train"].train_test_split(test_size=0.125, seed=42)