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@@ -20,17 +20,9 @@ task_ids:
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  - language-modeling
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  - masked-language-modeling
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  pretty_name: LexFiles
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- configs:
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- - eu_legislation
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- - eu_court_cases
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- - uk_legislation
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- - uk_court_cases
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- - us_legislation
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- - us_court_cases
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- - us_contracts
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- - canadian_legislation
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- - canadian_court_cases
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- - indian_court_cases
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  ---
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@@ -66,7 +58,7 @@ The corpus contains approx. 19 billion tokens. In comparison, the "Pile of Law"
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  | Indian Court Decisions | `indian-court-cases` | 34.8K | 111.6M | 0.6% | 3.4% | 6.9% |
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  | Canadian Legislation | `canadian-legislation` | 6K | 33.5M | 0.2% | 1.9% | 5.5% |
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  | Canadian Court Decisions | `canadian-court-cases` | 11.3K | 33.1M | 0.2% | 1.8% | 5.4% |
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- | U.S. Court Decisions [1] | `court-listener` | 4.6M | 11.4B | 59.2% | 34.7% | 17.5% |
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  | U.S. Legislation | `us-legislation` | 518 | 1.4B | 7.4% | 12.3% | 11.5% |
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  | U.S. Contracts | `us-contracts` | 622K | 5.3B | 27.3% | 23.6% | 15.0% |
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  | Total | `lexlms/lex_files` | 5.8M | 18.8B | 100% | 100% | 100% |
@@ -82,24 +74,37 @@ Additional corpora not considered for pre-training, since they do not represent
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  | Legal web pages from C4 | `legal-c4` | 284K | 340M |
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  ### Citation
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  [*Ilias Chalkidis\*, Nicolas Garneau\*, Catalina E.C. Goanta, Daniel Martin Katz, and Anders Søgaard.*
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  *LeXFiles and LegalLAMA: Facilitating English Multinational Legal Language Model Development.*
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- *2022. In the Proceedings of the 61th Annual Meeting of the Association for Computational Linguistics. Toronto, Canada.*](https://arxiv.org/abs/2305.07507)
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  ```
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- @inproceedings{chalkidis-garneau-etal-2023-lexlms,
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- title = {{LeXFiles and LegalLAMA: Facilitating English Multinational Legal Language Model Development}},
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- author = "Chalkidis*, Ilias and
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- Garneau*, Nicolas and
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- Goanta, Catalina and
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- Katz, Daniel Martin and
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- Søgaard, Anders",
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- booktitle = "Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics",
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- month = june,
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  year = "2023",
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  address = "Toronto, Canada",
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  publisher = "Association for Computational Linguistics",
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- url = "https://arxiv.org/abs/2305.07507",
 
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  }
 
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  ```
 
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  - language-modeling
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  - masked-language-modeling
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  pretty_name: LexFiles
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+ tags:
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+ - legal
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+ - law
 
 
 
 
 
 
 
 
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  ---
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  | Indian Court Decisions | `indian-court-cases` | 34.8K | 111.6M | 0.6% | 3.4% | 6.9% |
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  | Canadian Legislation | `canadian-legislation` | 6K | 33.5M | 0.2% | 1.9% | 5.5% |
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  | Canadian Court Decisions | `canadian-court-cases` | 11.3K | 33.1M | 0.2% | 1.8% | 5.4% |
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+ | U.S. Court Decisions [1] | `us-court-cases` | 4.6M | 11.4B | 59.2% | 34.7% | 17.5% |
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  | U.S. Legislation | `us-legislation` | 518 | 1.4B | 7.4% | 12.3% | 11.5% |
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  | U.S. Contracts | `us-contracts` | 622K | 5.3B | 27.3% | 23.6% | 15.0% |
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  | Total | `lexlms/lex_files` | 5.8M | 18.8B | 100% | 100% | 100% |
 
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  | Legal web pages from C4 | `legal-c4` | 284K | 340M |
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+ ### Usage
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+
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+ Load a specific sub-corpus, given the corpus alias, as presented above.
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+
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+ ```python
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+ from datasets import load_dataset
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+
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+ dataset = load_dataset('lexlms/lex_files', name='us-court-cases')
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+
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+ ```
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+
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  ### Citation
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  [*Ilias Chalkidis\*, Nicolas Garneau\*, Catalina E.C. Goanta, Daniel Martin Katz, and Anders Søgaard.*
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  *LeXFiles and LegalLAMA: Facilitating English Multinational Legal Language Model Development.*
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+ *2022. In the Proceedings of the 61th Annual Meeting of the Association for Computational Linguistics. Toronto, Canada.*](https://aclanthology.org/2023.acl-long.865/)
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  ```
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+ @inproceedings{chalkidis-etal-2023-lexfiles,
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+ title = "{L}e{XF}iles and {L}egal{LAMA}: Facilitating {E}nglish Multinational Legal Language Model Development",
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+ author = "Chalkidis, Ilias and
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+ Garneau, Nicolas and
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+ Goanta, Catalina and
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+ Katz, Daniel and
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+ S{\o}gaard, Anders",
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+ booktitle = "Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
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+ month = jul,
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  year = "2023",
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  address = "Toronto, Canada",
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  publisher = "Association for Computational Linguistics",
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+ url = "https://aclanthology.org/2023.acl-long.865",
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+ pages = "15513--15535",
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  }
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+
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  ```