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@@ -10,10 +10,10 @@ tags:
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  - pos
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  ---
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- # ud_fr_fqb_fr_prompt_pos
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  ## Summary
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- **ud_fr_fqb_fr_prompt_pos** is a subset of the [**Dataset of French Prompts (DFP)**]().
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  It contains **48,069** 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 fqb split by Seddah et Candito 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.
@@ -67,7 +67,7 @@ fr_fqb['test']['upos'] = list(map(lambda x: x.replace("[","").replace("]","").re
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  # How to use?
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  ```
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  from datasets import load_dataset
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- dataset = load_dataset("CATIE-AQ/ud_fr_fqb_fr_prompt_pos")
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  ```
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  # Citation
 
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  - pos
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  ---
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+ # universal_dependencies_fr_fqb_fr_prompt_pos
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  ## Summary
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+ **universal_dependencies_fr_fqb_fr_prompt_pos** is a subset of the [**Dataset of French Prompts (DFP)**]().
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  It contains **48,069** 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 fqb split by Seddah et Candito 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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  # How to use?
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  ```
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  from datasets import load_dataset
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+ dataset = load_dataset("CATIE-AQ/universal_dependencies_fr_fqb_fr_prompt_pos")
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  ```
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  # Citation