Librarian Bot: Add language metadata for dataset
Browse filesThis pull request aims to enrich the metadata of your dataset by adding language metadata to `YAML` block of your dataset card `README.md`.
How did we find this information?
- The librarian-bot downloaded a sample of rows from your dataset using the [dataset-server](https://huggingface.co/docs/datasets-server/) library
- The librarian-bot used a language detection model to predict the likely language of your dataset. This was done on columns likely to contain text data.
- Predictions for rows are aggregated by language and a filter is applied to remove languages which are very infrequently predicted
- A confidence threshold is applied to remove languages which are not confidently predicted
The following languages were detected with the following mean probabilities:
- English (en): 95.14%
If this PR is merged, the language metadata will be added to your dataset card. This will allow users to filter datasets by language on the [Hub](https://huggingface.co/datasets).
If the language metadata is incorrect, please feel free to close this PR.
To merge this PR, you can use the merge button below the PR:
![Screenshot 2024-02-06 at 15.27.46.png](https://cdn-uploads.huggingface.co/production/uploads/63d3e0e8ff1384ce6c5dd17d/1PRE3CoDpg_wfThC6U1w0.png)
This PR comes courtesy of [Librarian Bot](https://huggingface.co/librarian-bots). If you have any feedback, queries, or need assistance, please don't hesitate to reach out to
@davanstrien
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---
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license: apache-2.0
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dataset_info:
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configs:
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---
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A key question for understanding multimodal vs. language capabilities of models is what is
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language:
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- en
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license: apache-2.0
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dataset_info:
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- config_name: maze
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features:
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- name: id
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dtype: int32
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- name: image
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dtype: image
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- name: prompt
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dtype: string
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- name: ground_truth
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dtype: string
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- name: task
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dtype: string
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- name: question_type
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dtype: string
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- name: target_options
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dtype: string
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- config_name: maze_text_only
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features:
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- name: id
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dtype: int32
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- name: prompt
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dtype: string
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- name: ground_truth
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dtype: string
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- name: task
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dtype: string
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- name: question_type
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dtype: string
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- name: target_options
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dtype: string
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- config_name: spatial_grid
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features:
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- name: id
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dtype: int32
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- name: image
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dtype: image
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- name: prompt
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dtype: string
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- name: ground_truth
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dtype: string
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- name: task
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dtype: string
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- name: question_type
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dtype: string
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- name: target_options
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dtype: string
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- config_name: spatial_grid_text_only
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features:
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- name: id
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dtype: int32
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- name: prompt
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dtype: string
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- name: ground_truth
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dtype: string
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- name: task
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dtype: string
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- name: question_type
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dtype: string
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- name: target_options
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dtype: string
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- config_name: spatial_map
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features:
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- name: id
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dtype: int32
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- name: image
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dtype: image
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- name: prompt
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dtype: string
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- name: ground_truth
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dtype: string
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- name: task
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dtype: string
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- name: question_type
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dtype: string
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- name: target_options
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dtype: string
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- config_name: spatial_map_text_only
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features:
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- name: id
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dtype: int32
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- name: prompt
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dtype: string
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- name: ground_truth
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dtype: string
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- name: task
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dtype: string
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- name: question_type
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dtype: string
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- name: target_options
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dtype: string
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configs:
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- config_name: maze
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data_files:
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- split: val
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path: maze/maze_val.parquet
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- config_name: maze_text_only
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data_files:
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- split: val
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path: maze/maze_text_only_val.parquet
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- config_name: spatial_grid
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data_files:
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- split: val
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path: spatial_grid/spatial_grid_val.parquet
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- config_name: spatial_grid_text_only
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data_files:
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- split: val
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path: spatial_grid/spatial_grid_text_only_val.parquet
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- config_name: spatial_map
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data_files:
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- split: val
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path: spatial_map/spatial_map_val.parquet
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- config_name: spatial_map_text_only
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data_files:
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- split: val
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path: spatial_map/spatial_map_text_only_val.parquet
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---
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A key question for understanding multimodal vs. language capabilities of models is what is
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