Easy way to create a Kaggle dataset from a Huggingface dataset?
I'm not sure whether this is more appropriately addressed with HuggingFace or Kaggle.  I would like to somehow directly create a Kaggle dataset from a HuggingFace Dataset.

While Kaggle does provide the option to create a dataset from a URI, that URI must point to a single file.  For example:

![image](https://user-images.githubusercontent.com/5355286/235792394-7c559d07-4aff-45b7-ad2b-9c5280c88415.png)


Is there some mechanism from huggingface to represent a dataset (such as that from `load_dataset('wmt14', 'de-en', split='train')` as a single file?  Or, some other way to get that into a Kaggle dataset so that I can use the huggingface `datasets` module to process and consume it inside of a Kaggle notebook?

Thanks in advance!

Hi @hrbigelow , I'm no expert for such a question so I'll ping @lhoestq from the `datasets` library (also this issue could be moved there if someone with permission can do it :) ) Hi ! Many datasets are made of several files, and how they are parsed often requires a python script. Because of that, datasets like wmt14 are not available as a single file on HF. Though you can create this file using `datasets`:

```python
from datasets import load_dataset

ds = load_dataset("wmt14", "de-en", split="train")

ds.to_json("wmt14-train.json")
# OR to parquet, which is compressed:
# ds.to_parquet("wmt14-train.parquet")
```

We are also working on providing parquet exports for all datasets, but wmt14 is not supported yet (we're rolling it out for datasets <1GB first). They're usually available in the `refs/convert/parquet` branch (empty for wmt14):

<img width="267" alt="image" src="https://user-images.githubusercontent.com/42851186/235878909-7339f5a4-be19-4ada-85d8-8a50d23acf35.png">
 also cc @nateraw for visibility on this (and cc @osanseviero too) I've requested support for creating a Kaggle dataset from an imported HF dataset repo on their "forum" here: https://www.kaggle.com/discussions/product-feedback/427142 (upvotes appreciated 🙂)