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https://api.github.com/repos/huggingface/datasets/issues/193 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/193/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/193/comments | https://api.github.com/repos/huggingface/datasets/issues/193/events | https://github.com/huggingface/datasets/issues/193 | 624,655,558 | MDU6SXNzdWU2MjQ2NTU1NTg= | 193 | [Tensorflow] Use something else than `from_tensor_slices()` | {
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```python
columns = ['input_ids', 'token_type_ids', 'attention_mask', 'start_positions', 'end_positions']
train_tf_dataset.set_format(type='tensorflow', columns=columns)
features = {x: train_tf_dataset[x] for x in columns[:3]}
label... | {
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https://api.github.com/repos/huggingface/datasets/issues/192 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/192/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/192/comments | https://api.github.com/repos/huggingface/datasets/issues/192/events | https://github.com/huggingface/datasets/issues/192 | 624,397,592 | MDU6SXNzdWU2MjQzOTc1OTI= | 192 | [Question] Create Apache Arrow dataset from raw text file | {
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Is the worth of send it to you and add i... | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/190... | This PR add the Spanish Squad versions 1 and 2 datasets.
Fixes #164 | {
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https://api.github.com/repos/huggingface/datasets/issues/187 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/187/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/187/comments | https://api.github.com/repos/huggingface/datasets/issues/187/events | https://github.com/huggingface/datasets/issues/187 | 623,627,800 | MDU6SXNzdWU2MjM2Mjc4MDA= | 187 | [Question] How to load wikipedia ? Beam runner ? | {
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* `WARNING:nlp.builder:Trying to generate a dataset using Apache Beam, yet no Beam Runner or PipelineOptions() has been provided. Please pass a nlp.DownloadConfig(beam_runner=...) object to the builder.download_and_prepare(download_config=...) method. Default values will be ... | {
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https://api.github.com/repos/huggingface/datasets/issues/186 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/186/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/186/comments | https://api.github.com/repos/huggingface/datasets/issues/186/events | https://github.com/huggingface/datasets/issues/186 | 623,595,180 | MDU6SXNzdWU2MjM1OTUxODA= | 186 | Weird-ish: Not creating unique caches for different phases | {
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```python
import nlp
dataset = nlp.load_dataset('boolq')
def func1(x):
return x
def func2(x):
return None
train_output = dataset["train"].map(func1)
valid_output = dataset["validation"].map(func1)
print()
print(len(train_output), len(valid_output))
# Output: 9427 9427
```
Th... | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/185... | ### Dummy data command
This PR adds a new command `python nlp-cli dummy_data <path_to_dataset_folder>` that gives in-detail instructions on how to add the dummy data files.
It would be great if you can try it out by moving the current dummy_data folder of any dataset in `./datasets` with `mv datasets/<dataset_s... | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/184... | **`default __iter__ needs IndexError`**.
When I want to create a wrapper of arrow dataset to adapt to fastai,
I don't know how to initialize it, so I didn't use inheritance but use object composition.
I wrote sth like this.
```
clas HF_dataset():
def __init__(self, arrow_dataset):
self.dset = arrow_datas... | {
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ax = nlp.load_dataset('glue', 'ax')
for i in range(30): print(ax['test'][i]['label'], end=', ')
```
```
-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
``` | {
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It is supposed to work like this
- Register to get username, password at huggingface.co
- `nlp-cli login` and type username, passworld
- I have a single file to upload at `./ttc/ttc_freq_extra.csv`
- `nlp-cli upload ttc/ttc_freq_extra.csv`
... | {
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This makes it impossible to have several training sets, which can occur when:
- A dataset corresponds to a collection of sub-datasets
- A dataset was built in stages, adding new examples at each stage
Would it be ... | {
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I guess the manual download instructions for `xsum` can also be improved. | {
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The print function was not of much help I think.
We should think about adding a command that creates the dummy folder structure for the user. | {
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https://api.github.com/repos/huggingface/datasets/issues/175 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/175/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/175/comments | https://api.github.com/repos/huggingface/datasets/issues/175/events | https://github.com/huggingface/datasets/issues/175 | 621,929,428 | MDU6SXNzdWU2MjE5Mjk0Mjg= | 175 | [Manual data dir] Error message: nlp.load_dataset('xsum') -> TypeError | {
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```python
import nlp
xsum = nlp.load_dataset('xsum')
```
Issue is `dl_manager.manual_dir`is `None`
```python
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-42-8a32f06... | {
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Furthermore instead of extracting next to the dummy_data.zip file, we extract in the temp `cached_dir` used for tests, so that all the extracted directories get r... | {
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Please consider changing the folder name ....
Reference to folder -
nlp/datasets/cnn_dailymail/dummy/3.0.0/3.0.0/dummy_data-zip-extracted/dummy_data/uc?export=download&id=0BwmD_VLjROrfM1BxdkxVaTY2bWs/dailymail/s... | {
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This should fix #143
I tested with
```python3
predictions = [
{'id': '56be4db0acb8001400a502ec', 'prediction_text': 'Denver Broncos'}
]
references = [
{'answers': [{'text': 'Denver Broncos'}], 'id': '56be4db0acb8001400a502ec'}
]
``` | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/170... | What we have now as the `anli` dataset is actually the αNLI dataset from the ART challenge dataset. This name is confusing because `anli` is also the name of adversarial NLI (see [https://github.com/facebookresearch/anli](https://github.com/facebookresearch/anli)).
I renamed the current `anli` dataset by `art`. | {
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} | This PR adds the qanta question answering datasets from [Quizbowl: The Case for Incremental Question Answering](https://arxiv.org/abs/1904.04792) and [Trick Me If You Can: Human-in-the-loop Generation of Adversarial Question Answering Examples](https://www.aclweb.org/anthology/Q19-1029/) (adversarial fold)
This part... | {
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https://api.github.com/repos/huggingface/datasets/issues/168 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/168/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/168/comments | https://api.github.com/repos/huggingface/datasets/issues/168/events | https://github.com/huggingface/datasets/issues/168 | 620,959,819 | MDU6SXNzdWU2MjA5NTk4MTk= | 168 | Loading 'wikitext' dataset fails | {
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Code to reproduce (From example notebook):
import nlp
wikitext_dataset = nlp.load_dataset('wikitext')
Error:
---------------------------------------------------------------------------
AttributeError Traceback (most rece... | {
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https://api.github.com/repos/huggingface/datasets/issues/167 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/167/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/167/comments | https://api.github.com/repos/huggingface/datasets/issues/167/events | https://github.com/huggingface/datasets/pull/167 | 620,908,786 | MDExOlB1bGxSZXF1ZXN0NDIwMDY0NDMw | 167 | [Tests] refactor tests | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/167... | This PR separates AWS and Local tests to remove these ugly statements in the script:
```python
if "/" not in dataset_name:
logging.info("Skip {} because it is a canonical dataset")
return
```
To run a `aws` test, one should now run the following command:
```python
pytest -s... | {
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Also, we could maybe have a clear indication of which method modify in-place and which methods return/cache a modified dataset. I kinda like torch conversion of having an underscore suffix for all the methods which modify a dataset in-pl... | {
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https://api.github.com/repos/huggingface/datasets/issues/165 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/165/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/165/comments | https://api.github.com/repos/huggingface/datasets/issues/165/events | https://github.com/huggingface/datasets/issues/165 | 620,758,221 | MDU6SXNzdWU2MjA3NTgyMjE= | 165 | ANLI | {
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For ANLI, use https://github.com/facebookresearch/anli. As that paper says, "Our dataset is not
to be confused with abductive NLI (Bhagavatula et al., 2019), which calls itself αNLI, or ART.".
Indeed, the paper cited under what is currently called anli says in the abstract "We int... | {
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In order to cover multilingual support a little step could be adding standard Datasets used for Spanish NER and POS tasks.
I can provide it in raw and preprocessed formats. | {
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This makes sure it takes the previous files when computing the hash. | {
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I am working on a program that uses the `nlp` library with the `SST2` dataset.
The rough outline of the program is:
```
import nlp as nlp_datasets
...
parser.add_argument('--dataset', help='HuggingFace Datasets id', default=['glue', 'sst2'], nargs='+')
...
dataset = nlp_datasets.load_dataset(*args.... | {
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https://api.github.com/repos/huggingface/datasets/issues/158 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/158/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/158/comments | https://api.github.com/repos/huggingface/datasets/issues/158/events | https://github.com/huggingface/datasets/pull/158 | 620,396,658 | MDExOlB1bGxSZXF1ZXN0NDE5NjUyNTQy | 158 | add Toronto Books Corpus | {
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} | This PR adds the Toronto Books Corpus.
.
It on consider TMX and plain text files (Moses) defined in the table **Statistics and TMX/Moses Downloads** [here](http://opus.nlpl.eu/Books.php ) | {
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"TypeError: list_() takes exactly one argument (2 given)"
gist can be found here
https://gist.github.com/saahiluppal/c4b878f330b10b9ab9762bc0776c0a6a | {
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```
import nlp
dataset = nlp.load_dataset('wmt14')
print(dataset['train'][0])
```
```
Traceback (most recent call last):
File "/home/tom/.local/lib/python3.6/site-packages/IPython/core/interactiveshell.py", line 3326, in run_code
exec(code_obj, self.... | {
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this PR adds the WNUT 17 dataset to `nlp`.
> Emerging and Rare entity recognition
> This shared task focuses on identifying unusual, previously-unseen entities in the context of emerging discussions. Named entities form the basis of many modern approaches to other tasks (like event clustering and summarisati... | {
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In Colab,
```
%pip install -q nlp
%pip install -q apache_beam mwparserfromhell
dataset = nlp.load_dataset('wikipedia')
```
get
```
Downloading and preparing dataset wikipedia/20200501.aa (download: Unknown size, generated: Unknown size, total: Unknown size) to /root/.cache/huggingface/datasets/w... | {
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] | closed | false | null | [] | null | [] | 2020-05-17T00:28:24Z | 2020-06-18T16:23:23Z | 2020-06-18T16:23:23Z | NONE | null | null | null | It would be nice if we could use sklearn `train_test_split` to quickly generate subsets from the dataset objects returned by `nlp.load_dataset`. At the moment the code:
```python
data = nlp.load_dataset('imdb', cache_dir=data_cache)
f_half, s_half = train_test_split(data['train'], test_size=0.5, random_state=seed)... | {
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Here is an example of how to use it.
```sh
import nlp
bertscore = nlp.load_metric('metrics/bertscore') # or simply nlp.load_metric('bertscore') after this is added to huggingface's s3 bucket
predictions = ['example', 'fruit']
references = [[... | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/145... | I forgot to add this line in PR #145 . | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/144... | AWS tests should in general not run for canonical datasets. Only local tests will run in this case. This way a PR is able to pass when adding a new dataset.
This PR changes to logic to the following:
1) All datasets that are present in `nlp/datasets` are tested only locally. This way when one adds a canonical da... | {
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```
ArrowTypeError: Could not convert [{'text': 'Denver Broncos'}, {'text': 'Denver Broncos'}, {'text': 'Denver Broncos'}] with type list: was not a dict, tuple, or recognized null value for conversion to struct type
```
This is how my predictions and references lo... | {
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The datasets are fully functional though for the "big" languag... | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/140... | This PR also enables local tests by default
I think it's safer for now to enable both local and aws tests for every commit. The problem currently is that when we do a PR to add a dataset, the dataset is not yet on AWS on therefore not tested on the PR itself. Thus the PR will always be green even if the datasets are... | {
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this PR adds the GermEval 2014 NER dataset 😃
> The GermEval 2014 NER Shared Task builds on a new dataset with German Named Entity annotation [1] with the following properties:
> - The data was sampled from German Wikipedia and News Corpora as a collection of citations.
> - The dataset covers over 31,000... | {
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Just making a thread here recording what I said on Twitter, as it's impossible to follow discussion there. It's also just really not a good way to talk about this sort of thing.
The issue is that modules go into the global namespace, so you shouldn't use variable names that conflict with module names. This... | {
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It appears to be possible to point to a local dataset path rather than downloading the external ones, but I'm not exactly sure how to go about doing this.
... | {
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More information and the download link are available [here](https://skylion007.github.io/OpenWebTextCorpus/). | {
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```python
dataset = nlp.load_dataset('glue')
```
The resultant dataset seems to be CoLA be default, without throwing any error. This is in contrast to calling:
```python
metric = nlp.load_metric("glue")
```
which throws an error telling the user that they need to specify a task in GLUE. Should the... | {
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I am going through [this overview notebook](https://colab.research.google.com/github/huggingface/nlp/blob/master/notebooks/Overview.ipynb)
In simple step `dataset = nlp.load_dataset('squad', split='validation[:10%]')`
I get an error, which is connected with some inner code, I think:
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Our first dataset script that only lives on AWS :-) https://s3.console.aws.amazon.com/s3/buckets/datasets.huggingface.co/nlp/datasets/webis/tl_dr/?region=us-east-1 @julien-c @jplu | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/123... | ## Change default Test from local => aws
As a default we set` aws=True`, `Local=False`, `slow=False`
### 1. RUN_AWS=1 (default)
This runs 4 tests per dataset script.
a) Does the dataset script have a valid etag / Can it be reached on AWS?
b) Can we load its `builder_class`?
c) Can we load **all** dataset c... | {
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[Here is the colab notebook I'm using.](https://colab.research.google.com/drive/1YH4JCAy0R1MMSc-k_Vlik_s1LEzP_t1h?usp=sharing)
```python
import nlp
dataset = nlp.load_dataset('squad', split='validation[:10%]')
def test(sample):
samp... | {
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[Colab notebook](https://colab.research.google.com/drive/11Mf7iNhIyt6GpgA1dBEtg3cyMHmMhtZS?usp=sharing)
But I meet this error :
> AttributeError: type object 'pyarrow.lib.RecordBatch' has no attribute 'from_struct_array'
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Should I apply my map function on the subsets one by one ?
```python
import nlp
cnn_dm = nlp.load_dataset('cnn_dailymail')
for corpus in ['train', 'test', 'validation']:
cnn_dm[corpus] = cnn_dm[corpus].map(my_f... | {
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```python
dataset.drop('id')
```
But I didn't find how to remove a specific row.
**For example, how can I remove all sample w... | {
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"color": "25b21e",
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"name": "metric bug",
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"url": "https://api.github.com/repos/huggingface/datasets/labels/metric%20bug"
}
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I have to files : `test.pred.tokenized` and `test.gold.tokenized` with each line containing a sentence.
I tried :
```python
import nlp
rouge = nlp.load_metric('rouge')
with open("test.pred.tokenized") as p, open("test.gold.tokenized") as g:
for lp, lg in zip(p, g):
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```python
cnn_dm = nlp.load_dataset('cnn_dailymail')
print(cnn_dm.info)
```
returns :
> AttributeError: 'dict' object has no attribute 'info' | {
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```python
import nlp
assert "cnn_dailymail" in [dataset.id for dataset in nlp.list_datasets()]
cnn_dm = nlp.load_dataset('cnn_dailymail')
```
[Colab notebook](https://colab.research.google.com/drive/1zQ3bYAVzm1h0mw0yWPqKAg_4EUlSx5Ex?usp=sharing)
gives following error ... | {
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I had to do add some minor hacks to an important function to make it work.
There might be a cleaner way to handle it - can you take a look @thomwolf ? | {
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The user can then store these files under a hard-coded name: `wikihowAll.csv` and `wikihowSep.csv` in this case in a directory of his choice, e.g. `~/wikihow/manual_dir`.
The dataset ca... | {
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```python
import nlp
met = nlp.load_metric('metrics/seqeval')
references = [['O', 'O', 'O', 'B-MISC', 'I-MISC', 'I-MISC', 'O'], ['B-PER', 'I-PER', 'O']]
predictions = [['O', 'O', 'B-MISC', 'I-MISC', 'I-MISC', 'I-MISC', 'O'], ['B-... | {
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} | ### Better verifications when loading a dataset
I replaced the `urls_checksums` directory that used to contain `checksums.txt` and `cached_sizes.txt`, by a single file `dataset_infos.json`. It's just a dict `config_name` -> `DatasetInfo`.
It simplifies and improves how verifications of checksums and splits sizes ... | {
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