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- ---
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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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- - split: test
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- path: data/test-*
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- dataset_info:
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- features:
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- - name: prompt
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- dtype: string
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- - name: prompt_id
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- dtype: string
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- - name: messages
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- list:
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- - name: content
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- dtype: string
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- - name: role
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- dtype: string
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- - name: category
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- dtype: string
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- splits:
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- - name: train
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- num_bytes: 16496867
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- num_examples: 9500
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- - name: test
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- num_bytes: 887460
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- num_examples: 500
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- download_size: 11045587
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- dataset_size: 17384327
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- ---
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  This is a converted version of the no_robots dataset into Tulu SFT training format.
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  The conversion script can be found in our [open-instruct](https://github.com/allenai/open-instruct/blob/main/scripts/data/sft/no_robots.py) repo.
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  The conversion took the following parameters:
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  - apply_keyword_filters: False
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- - apply_empty_message_filters: True
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  - push_to_hub: True
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  - hf_entity: ai2-adapt-dev
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  - converted_dataset_name: no_robots_converted
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  This is a converted version of the no_robots dataset into Tulu SFT training format.
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  The conversion script can be found in our [open-instruct](https://github.com/allenai/open-instruct/blob/main/scripts/data/sft/no_robots.py) repo.
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  The conversion took the following parameters:
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  - apply_keyword_filters: False
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+ - apply_empty_message_filters: False
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  - push_to_hub: True
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  - hf_entity: ai2-adapt-dev
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  - converted_dataset_name: no_robots_converted