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README.md
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- text-generation
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- table-question-answering
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- summarization
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size_categories:
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- 1K<n<10K
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# Code des assurances, non-instruct (
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This project focuses on fine-tuning pre-trained language models to create efficient and accurate models for legal practice.
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- `instruction`: `string`, presenting the instruction linked to the element.
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- `input`: `string`, signifying the input details for the element.
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- `output`: `string`, indicating the output information for the element.
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We used the following list of instructions for generating the dataset:
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```python
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```
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## Citing this project
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If you use this code in your research, please use the following BibTeX entry.
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```BibTeX
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@misc{louisbrulenaudet2023,
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author = {Louis Brulé Naudet},
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title = {Code des assurances, non-instruct (11-12-2023)},
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howpublished = {\url{https://huggingface.co/datasets/louisbrulenaudet/code-assurances}},
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year = {2023}
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}
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```
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## Feedback
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If you have any feedback, please reach out at [[email protected]](mailto:[email protected]).
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- text-generation
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- table-question-answering
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- summarization
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- text-retrieval
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- question-answering
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- text-classification
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size_categories:
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- 1K<n<10K
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---
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# Code des assurances, non-instruct (2024-03-25)
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This project focuses on fine-tuning pre-trained language models to create efficient and accurate models for legal practice.
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- `instruction`: `string`, presenting the instruction linked to the element.
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- `input`: `string`, signifying the input details for the element.
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- `output`: `string`, indicating the output information for the element.
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- `start`: `string`, the date of entry into force of the article.
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- `expiration`: `string`, the date of expiration of the article.
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- `num`: `string`, the id of the article.
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We used the following list of instructions for generating the dataset:
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```python
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]
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```
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## Feedback
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If you have any feedback, please reach out at [[email protected]](mailto:[email protected]).
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