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Download README.md from stas/openwebtext-10k: direct link, hf CLI and curl.
- Browser
- Download file 951 Bytes
-
https://huggingface.co/datasets/stas/openwebtext-10k/resolve/152771d7ae284673c3ad7ffdd9b3afc2741f1d00/README.md
- Command line
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hf download hf://datasets/stas/openwebtext-10k@152771d7ae284673c3ad7ffdd9b3afc2741f1d00/README.md
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curl -L -o README.md https://huggingface.co/datasets/stas/openwebtext-10k/resolve/152771d7ae284673c3ad7ffdd9b3afc2741f1d00/README.md
951 Bytes
10K slice of OpenWebText - An open-source replication of the WebText dataset from OpenAI.
This is a small subset representing the first 10K records from the original dataset - created for testing.
The full 8M-record dataset is here.
$ python -c "from datasets import load_dataset; ds=load_dataset('stas/openwebtext-10k'); print(ds)"
DatasetDict({
train: Dataset({
features: ['text'],
num_rows: 10000
})
})
- Records: 10,000
- compressed size: ~15MB
- uncompressed size: 50MB
To convert to jsonlines:
from datasets import load_dataset
dataset_name = "stas/openwebtext-10k"
name = dataset_name.split('/')[-1]
ds = load_dataset(dataset_name, split='train')
ds.to_json(f"{name}.jsonl", orient="records", lines=True)
To see how this subset was created, here is the instructions file.