Partial OpenWebText Download Explained | Generated by AI
Short answer: No, it does NOT download the entire OpenWebText. It only fetches the slice you request. And yes, you can see download progress — Hugging Face shows it automatically unless you suppress logs.
Here’s the breakdown:
Does load_dataset("openwebtext", split="train[:10000]") download the full dataset?
It downloads only the shards needed for that slice, not the full corpus.
OpenWebText on Hugging Face is stored in multiple shards (e.g., dozens of .jsonl.zst files). When you load only the first 10,000 rows, the library downloads just enough shards to cover those examples.
It does not download all shards.
So the download is proportional to the amount of data you actually load.
How to see its download progress
You normally see console progress bars like:
Downloading (…)arrow…: 100%
Downloading (…)nload: 100%
Extracting…: 100%
Generating train split…: 100%
If logs are suppressed or you want more visibility, use:
from datasets import load_dataset
import datasets
datasets.logging.set_verbosity_info()
dataset = load_dataset("openwebtext", split="train[:10000]")
This ensures progress bars always show.
How to see how much it downloaded
After loading:
dataset._info
or:
dataset.info
Also, Hugging Face stores files under:
~/.cache/huggingface/datasets/
You can check disk usage with:
du -sh ~/.cache/huggingface/datasets
Optional: force verbose debug logs
If you want extremely detailed logs:
datasets.logging.set_verbosity_debug()
Why this matters for NanoGPT
NanoGPT’s training snippets use:
dataset = load_dataset("openwebtext", split="train[:10000]")
to avoid huge downloads during testing. Good news: the behavior matches exactly what you want — fast, partial download.
If you want, I can show:
- How to preview data before download
- How to load OpenWebText locally
- How to check how many shards your slice touches