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  ---
 
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  language:
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  - fr
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- license: apache-2.0
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  multilinguality:
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  - monolingual
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- size_categories:
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- - 1K<n<10K
 
 
 
 
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  source_datasets:
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  - original
 
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  task_categories:
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  - text-generation
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  - table-question-answering
@@ -15,40 +20,10 @@ task_categories:
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  - text-retrieval
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  - question-answering
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  - text-classification
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- pretty_name: Code du tourisme
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- tags:
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- - finetuning
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- - legal
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- - french law
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- - droit français
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- - Code du tourisme
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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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- dataset_info:
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- features:
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- - name: instruction
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- dtype: string
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- - name: input
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- dtype: string
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- - name: output
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- dtype: string
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- - name: start
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- dtype: string
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- - name: expiration
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- dtype: string
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- - name: num
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- dtype: string
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- splits:
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- - name: train
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- num_bytes: 541436
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- num_examples: 648
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- download_size: 203551
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- dataset_size: 541436
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  ---
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- # Code du tourisme, non-instruct (2024-08-12)
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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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  ---
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+ license: apache-2.0
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  language:
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  - fr
 
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  multilinguality:
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  - monolingual
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+ tags:
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+ - finetuning
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+ - legal
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+ - french law
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+ - droit français
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+ - Code du tourisme
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  source_datasets:
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  - original
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+ pretty_name: Code du tourisme
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  task_categories:
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  - text-generation
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  - table-question-answering
 
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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 du tourisme, non-instruct (2024-08-13)
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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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