|
--- |
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dataset_info: |
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features: |
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- name: text |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 45957987986 |
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num_examples: 16896817 |
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download_size: 21312867175 |
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dataset_size: 45957987986 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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task_categories: |
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- text-generation |
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language: |
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- fa |
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pretty_name: 'HmBlogs: A big general Persian corpus' |
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size_categories: |
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- 10M<n<100M |
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--- |
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|
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# HmBlogs: A big general Persian corpus |
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HmBlogs is a general Persian corpus collected from nearly 20 million blog posts over a period of 15 years containig 6.8 billion tokens. |
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This version is the **preprocessed version** of the dataset prepared by the original authors and converted to proper format to integrate with 🤗Datasets. |
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In order to access the raw versions visit the official link at http://nlplab.sbu.ac.ir/hmBlogs-v3 . |
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|
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**Paper:** https://arxiv.org/abs/2111.02362 <br> |
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**Authors:** Hamzeh Motahari Khansari, Mehrnoush Shamsfard <br> |
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**Original Link:** http://nlplab.sbu.ac.ir/hmBlogs-v3/<br> |
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|
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## Usage |
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This dataset can be used for masked/causal language modeling. You can easily load this dataset like below: |
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|
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```python |
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from datasets import load_dataset |
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# Load the whole dataset |
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dataset = load_dataset("arxyzan/hmblogs-v3", split="train") |
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|
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# Load a portion by % |
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dataset = load_dataset("arxyzan/hmblogs-v3", split="train[:50%]") |
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|
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# Load a custom shard |
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dataset = load_dataset("arxyzan/hmblogs-v3", data_files=["data/train-00000-of-00046.parquet", "data/train-00001-of-00046.parquet"]) |
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``` |
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|
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# Citation |
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```cite |
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@article{DBLP:journals/corr/abs-2111-02362, |
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author = {Hamzeh Motahari Khansari and |
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Mehrnoush Shamsfard}, |
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title = {HmBlogs: {A} big general Persian corpus}, |
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journal = {CoRR}, |
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volume = {abs/2111.02362}, |
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year = {2021}, |
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url = {https://arxiv.org/abs/2111.02362}, |
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eprinttype = {arXiv}, |
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eprint = {2111.02362}, |
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timestamp = {Fri, 05 Nov 2021 15:25:54 +0100}, |
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biburl = {https://dblp.org/rec/journals/corr/abs-2111-02362.bib}, |
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bibsource = {dblp computer science bibliography, https://dblp.org} |
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} |
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``` |
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|
