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stanfordnlp

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sst

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Stanford NLP 127

Please paste the entire stack trace, not just the last part

Thanks for reporting, @henningheyen .

The source data (https://nlp.stanford.edu/~socherr/stanfordSentimentTreebank.zip) is unavailable due to SRCF datacenter shutdown: https://cs.stanford.edu/srcf_404

More info about SRCF Shutdown here: https://srcc.stanford.edu/srcf-shutdown

The outage is expected to be between Jun 24th to July 3rd. Afterwards, the loading of this dataset should work. Please feel free to ping if that is not the case.

The dataset loading is working now.

Please pass the argument download_mode="force_redownload" so that you force the redownload of the source data file (and delete the malformed cache file):

In [ 1]: from datasets import load_dataset; 

In [ 2]: ds = load_dataset("sst", download_mode="force_redownload")
No config specified, defaulting to: sst/default
Downloading and preparing dataset sst/default to .../.cache/huggingface/datasets/sst/default/1.0.0/b8a7889ef01c5d3ae8c379b84cc4080f8aad3ac2bc538701cbe0ac6416fb76ff...
Downloading data: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6.37M/6.37M [00:04<00:00, 1.49MB/s]
Downloading data: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 790k/790k [00:01<00:00, 430kB/s]
Dataset sst downloaded and prepared to .../.cache/huggingface/datasets/sst/default/1.0.0/b8a7889ef01c5d3ae8c379b84cc4080f8aad3ac2bc538701cbe0ac6416fb76ff. Subsequent calls will reuse this data. 
100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 263.82it/s]

In [ 3]: ds
Out[3]: 
DatasetDict({
    train: Dataset({
        features: ['sentence', 'label', 'tokens', 'tree'],
        num_rows: 8544
    })
    validation: Dataset({
        features: ['sentence', 'label', 'tokens', 'tree'],
        num_rows: 1101
    })
    test: Dataset({
        features: ['sentence', 'label', 'tokens', 'tree'],
        num_rows: 2210
    })
})