Datasets:

imthanhlv
/

binhvq_dedup

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The dataset viewer is not available for this dataset.

Cannot get the config names for the dataset.

Error code:   ConfigNamesError
Exception:    ImportError
Message:      To be able to use imthanhlv/binhvq_dedup, you need to install the following dependency: lm_dataformat.
Please install it using 'pip install lm_dataformat' for instance.
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 66, in compute_config_names_response
                  config_names = get_dataset_config_names(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 347, in get_dataset_config_names
                  dataset_module = dataset_module_factory(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1914, in dataset_module_factory
                  raise e1 from None
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1880, in dataset_module_factory
                  return HubDatasetModuleFactoryWithScript(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1504, in get_module
                  local_imports = _download_additional_modules(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 354, in _download_additional_modules
                  raise ImportError(
              ImportError: To be able to use imthanhlv/binhvq_dedup, you need to install the following dependency: lm_dataformat.
              Please install it using 'pip install lm_dataformat' for instance.

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BinhVQ dedup

Important: Please install lm_dataformat by pip install lm_dataformat before using this dataset

How to use

import datasets

dataset = datasets.load_dataset("imthanhlv/binhvq_dedup")

Dataset information

This dataset was created from https://github.com/binhvq/news-corpus dump with date 21/05/2021. I applied some simple preprocessing:

Using BeautifulSoup to clean content
Each record is concatenate of (title + "\n" + sapo + "\n" + content)
Then perform shuffling + split train & validation + deduplicate (exact match using sha256)

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