Librarian Bot: Add language metadata for dataset

This 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): 80.95%


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:

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
.

README.md

@@ -1,4 +1,10 @@
 ---
+language:
+- en
+size_categories:
+- 1K<n<10K
+task_categories:
+- text-generation
 dataset_info:
 - config_name: clj
   features:
@@ -547,12 +553,8 @@ configs:
   data_files:
   - split: test
     path: ts/test-*
-task_categories:
-- text-generation
 tags:
 - code
-size_categories:
-- 1K<n<10K
 ---
 
 This dataset contains the `humaneval` transpiled splits from `nuprl/MultiPL-E` dataset and is made available separately purely for the convenience of the [vllm-code-harness](https://github.com/iNeil77/vllm-code-harness) package. Specifically, it takes the `v3.0.0` splits of the original dataset but also retains the `humaneval-py` split form `v2.1.0`.