filter dataset based on licenses

README.md

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----
-dataset_info:
-  features:
-  - name: id
-    dtype: string
-  - name: title
-    dtype: string
-  - name: abstract
-    dtype: string
-  - name: authors
-    dtype: string
-  - name: published_date
-    dtype: string
-  - name: link
-    dtype: string
-  - name: markdown
-    dtype: string
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-    num_examples: 138380
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-  dataset_size: 6952989384
-configs:
-- config_name: default
-  data_files:
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-    path: data/train-*
-license: cc-by-nc-sa-4.0
----
-## Arxiver Dataset
-Arxiver consists of 138,830 [arXiv](https://arxiv.org/) papers converted to multi-markdown (**.mmd**) format. Our dataset includes original arXiv article IDs, titles, abstracts, authors, publication dates, URLs and corresponding markdown files published between January 2023 and October 2023.
-
-We hope our dataset will be useful for various applications such as semantic search, domain specific language modeling, question answering and summarization.
-
-## Curation
-The Arxiver dataset is created using a neural OCR - [Nougat](https://facebookresearch.github.io/nougat/). After OCR processing, we apply custom text processing steps to refine the data. This includes extracting author information, removing reference sections, and performing additional cleaning and formatting.
-
-## Using Arxiver
-You can easily download and use the arxiver dataset with Hugging Face's [datasets](https://huggingface.co/datasets) library.
-```py
-from datasets import load_dataset
-
-# whole dataset takes 3.3GB
-dataset = load_dataset("neuralwork/arxiver") 
-print(dataset)
-```
-
-Alternatively, you can stream the dataset to save disk space or to partially download the dataset:
-```py
-from datasets import load_dataset
-
-dataset = load_dataset("neuralwork/arxiver", streaming=True)
-print(dataset)
-print(next(iter(dataset['train'])))
-```
-
-## References
-The original articles are maintained by [arXiv](https://arxiv.org/) and copyrighted to the original authors, please refer to the arXiv license information [page](https://info.arxiv.org/help/license/index.html) for details. We release our dataset with a Creative Commons Attribution-Noncommercial-ShareAlike (CC BY-NC-SA 4.0) license, if you use this dataset in your research or project, please cite it as follows:
-```
-@misc{acar_arxiver2024,
-  author = {Alican Acar, Alara Dirik, Muhammet Hatipoglu},
-  title = {ArXiver},
-  year = {2024},
-  publisher = {Hugging Face},
-  howpublished = {\url{https://huggingface.co/datasets/neuralwork/arxiver}}
-}
-```

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