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@@ -8,14 +8,24 @@ task_categories:
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  - token-classification
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  tags:
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  - pos
 
 
 
 
 
 
 
 
 
 
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  ---
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  # universal_dependencies_fr_gsd_fr_prompt_pos
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  ## Summary
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- **universal_dependencies_fr_gsd_fr_prompt_pos** is a subset of the [**Dataset of French Prompts (DFP)**]().
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- It contains **X** rows that can be used for a part-of-speech task.
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- The original data (without prompts) comes from the dataset [universal_dependencies](https://huggingface.co/datasets/universal_dependencies) where only the French gsd split has been kept.
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  A list of prompts (see below) was then applied in order to build the input and target columns and thus obtain the same format as the [xP3](https://huggingface.co/datasets/bigscience/xP3) dataset by Muennighoff et al.
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@@ -60,9 +70,9 @@ fr_gsd['train']['upos'] = list(map(lambda x: x.replace("[","").replace("]","").r
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  # Splits
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- - train with X samples
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- - dev with Y samples
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- - test with Z samples
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  # How to use?
 
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  - token-classification
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  tags:
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  - pos
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+ - DFP
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+ - french prompts
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+ annotations_creators:
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+ - found
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+ language_creators:
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+ - found
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+ multilinguality:
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+ - monolingual
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+ source_datasets:
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+ - universal_dependencies_fr_gsd
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  ---
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  # universal_dependencies_fr_gsd_fr_prompt_pos
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  ## Summary
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+ **universal_dependencies_fr_gsd_fr_prompt_pos** is a subset of the [**Dataset of French Prompts (DFP)**](https://huggingface.co/datasets/CATIE-AQ/DFP).
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+ It contains **343,161** rows that can be used for a part-of-speech task.
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+ The original data (without prompts) comes from the dataset [universal_dependencies](https://huggingface.co/datasets/universal_dependencies) where only the French gsd split has been kept.
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  A list of prompts (see below) was then applied in order to build the input and target columns and thus obtain the same format as the [xP3](https://huggingface.co/datasets/bigscience/xP3) dataset by Muennighoff et al.
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  # Splits
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+ - `train` with 303,429 samples
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+ - `valid` with 30,996 samples
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+ - `test` with 8,736 samples
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  # How to use?