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https://api.github.com/repos/huggingface/datasets/issues/176 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/176/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/176/comments | https://api.github.com/repos/huggingface/datasets/issues/176/events | https://github.com/huggingface/datasets/pull/176 | 621,934,638 | MDExOlB1bGxSZXF1ZXN0NDIwODkzNDky | 176 | [Tests] Refactor MockDownloadManager | {
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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)
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https://api.github.com/repos/huggingface/datasets/issues/174 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/174/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/174/comments | https://api.github.com/repos/huggingface/datasets/issues/174/events | https://github.com/huggingface/datasets/issues/174 | 621,928,403 | MDU6SXNzdWU2MjE5Mjg0MDM= | 174 | nlp.load_dataset('xsum') -> TypeError | {
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https://api.github.com/repos/huggingface/datasets/issues/173 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/173/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/173/comments | https://api.github.com/repos/huggingface/datasets/issues/173/events | https://github.com/huggingface/datasets/pull/173 | 621,764,932 | MDExOlB1bGxSZXF1ZXN0NDIwNzUyNzQy | 173 | Rm extracted test dirs | {
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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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https://api.github.com/repos/huggingface/datasets/issues/172 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/172/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/172/comments | https://api.github.com/repos/huggingface/datasets/issues/172/events | https://github.com/huggingface/datasets/issues/172 | 621,377,386 | MDU6SXNzdWU2MjEzNzczODY= | 172 | Clone not working on Windows environment | {
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"gists... | null | 2 | 2020-05-20T00:45:14Z | 2020-05-23T12:49:13Z | 2020-05-23T11:27:52Z | CONTRIBUTOR | null | Cloning in a windows environment is not working because of use of special character '?' in folder name ..
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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https://api.github.com/repos/huggingface/datasets/issues/171 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/171/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/171/comments | https://api.github.com/repos/huggingface/datasets/issues/171/events | https://github.com/huggingface/datasets/pull/171 | 621,199,128 | MDExOlB1bGxSZXF1ZXN0NDIwMjk0ODM0 | 171 | fix squad metric format | {
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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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I renamed the current `anli` dataset by `art`. | {
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This part... | {
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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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```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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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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.
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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https://api.github.com/repos/huggingface/datasets/issues/150 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/150/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/150/comments | https://api.github.com/repos/huggingface/datasets/issues/150/events | https://github.com/huggingface/datasets/pull/150 | 619,809,645 | MDExOlB1bGxSZXF1ZXN0NDE5MTgyODU4 | 150 | Add WNUT 17 NER dataset | {
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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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] | closed | false | null | [] | null | 1 | 2020-05-17T15:42:39Z | 2020-05-18T17:01:46Z | 2020-05-18T17:01:46Z | NONE | null | https://github.com/rkadlec/ubuntu-ranking-dataset-creator or http://dataset.cs.mcgill.ca/ubuntu-corpus-1.0/ | {
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] | closed | false | null | [] | null | 2 | 2020-05-17T01:48:53Z | 2020-05-18T07:38:33Z | 2020-05-18T07:38:33Z | CONTRIBUTOR | null | # Reproduce
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 | 2 | 2020-05-17T00:28:24Z | 2020-06-18T16:23:23Z | 2020-06-18T16:23:23Z | NONE | 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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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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] | closed | false | null | [] | null | 1 | 2020-05-16T12:06:37Z | 2020-05-22T13:38:52Z | 2020-05-22T13:36:48Z | MEMBER | null | `squad_metric.compute` is giving following error
```
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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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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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",
"default": false,
"description": "A bug in a metric script",
"id": 2067393914,
"name": "metric bug",
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"url": "https://api.github.com/repos/huggingface/datasets/labels/metric%20bug"
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] | closed | false | null | [] | null | 5 | 2020-05-15T01:12:06Z | 2020-05-28T23:43:07Z | 2020-05-28T23:43:07Z | NONE | null | I'm trying to use rouge metric.
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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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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https://api.github.com/repos/huggingface/datasets/issues/93 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/93/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/93/comments | https://api.github.com/repos/huggingface/datasets/issues/93/events | https://github.com/huggingface/datasets/pull/93 | 617,522,029 | MDExOlB1bGxSZXF1ZXN0NDE3NDIxODUy | 93 | Cleanup notebooks and various fixes | {
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- WMT is the first dataset that uses an abstract class IMO, so I had to modify the `load_dataset_module` a bit. | {
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https://api.github.com/repos/huggingface/datasets/issues/91 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/91/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/91/comments | https://api.github.com/repos/huggingface/datasets/issues/91/events | https://github.com/huggingface/datasets/pull/91 | 617,339,484 | MDExOlB1bGxSZXF1ZXN0NDE3Mjc0MjA0 | 91 | [Paracrawl] add paracrawl | {
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- Also this PR reformats all dataset scripts and adds `datasets` to `make style` | {
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```python
nlp.list_datasets()
nlp.list_metrics()
# Copy and prepare the scripts at `local_path` for easy inspection/modification.
nlp.inspect_dataset(path, local_path)
# Copy and prepare the scripts at `local_path` for easy... | {
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I tested it on a small config and it works fine | {
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https://api.github.com/repos/huggingface/datasets/issues/87 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/87/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/87/comments | https://api.github.com/repos/huggingface/datasets/issues/87/events | https://github.com/huggingface/datasets/pull/87 | 617,267,118 | MDExOlB1bGxSZXF1ZXN0NDE3MjE1NzA0 | 87 | Add Flores | {
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This one was uses `tf.io.gfile.copy` to download the data but I added the support for custom download in the mock_download_manager. I also had to add a `tensorflow` dependency for tests. | {
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The result looks like this:
![Screenshot from 2020-05-12 18-34-43](https://user-images.githubusercontent.com/23423619/81721933-ee1faf00-9480-11ea-9e95-d6557cbd0c... | {
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https://api.github.com/repos/huggingface/datasets/issues/81 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/81/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/81/comments | https://api.github.com/repos/huggingface/datasets/issues/81/events | https://github.com/huggingface/datasets/pull/81 | 616,793,010 | MDExOlB1bGxSZXF1ZXN0NDE2ODM1NzE1 | 81 | add tests | {
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I also removed unused utils functions. | {
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https://api.github.com/repos/huggingface/datasets/issues/80 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/80/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/80/comments | https://api.github.com/repos/huggingface/datasets/issues/80/events | https://github.com/huggingface/datasets/pull/80 | 616,786,803 | MDExOlB1bGxSZXF1ZXN0NDE2ODMwNjk3 | 80 | Add nbytes + nexamples check | {
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Now when you do `save_checksums`, it also create `cached_sizes.txt` right next to the checksum file.
This new file stores the bytes sizes and the number of examples of each split that has been prepared and stored in the cache. Example:
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# Cached sizes: <full_config_name> <n... | {
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https://api.github.com/repos/huggingface/datasets/issues/79 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/79/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/79/comments | https://api.github.com/repos/huggingface/datasets/issues/79/events | https://github.com/huggingface/datasets/pull/79 | 616,785,613 | MDExOlB1bGxSZXF1ZXN0NDE2ODI5NzMy | 79 | [Convert] add new pattern | {
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https://api.github.com/repos/huggingface/datasets/issues/78 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/78/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/78/comments | https://api.github.com/repos/huggingface/datasets/issues/78/events | https://github.com/huggingface/datasets/pull/78 | 616,774,275 | MDExOlB1bGxSZXF1ZXN0NDE2ODIwNzU5 | 78 | [Tests] skip beam dataset tests for now | {
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https://api.github.com/repos/huggingface/datasets/issues/77 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/77/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/77/comments | https://api.github.com/repos/huggingface/datasets/issues/77/events | https://github.com/huggingface/datasets/pull/77 | 616,674,601 | MDExOlB1bGxSZXF1ZXN0NDE2NzQwMjAz | 77 | New datasets | {
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https://api.github.com/repos/huggingface/datasets/issues/76 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/76/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/76/comments | https://api.github.com/repos/huggingface/datasets/issues/76/events | https://github.com/huggingface/datasets/pull/76 | 616,579,228 | MDExOlB1bGxSZXF1ZXN0NDE2NjYyMTk2 | 76 | pin flake 8 | {
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