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https://api.github.com/repos/huggingface/datasets/issues/1454 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1454/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1454/comments | https://api.github.com/repos/huggingface/datasets/issues/1454/events | https://github.com/huggingface/datasets/pull/1454 | 761,199,862 | MDExOlB1bGxSZXF1ZXN0NTM1OTAxNjk4 | 1,454 | Add kinnews_kirnews | {
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} | [] | closed | false | null | [] | null | 1 | 2020-12-10T12:29:08 | 2020-12-17T18:34:16 | 2020-12-17T18:34:16 | CONTRIBUTOR | null | Add kinnews and kirnews | {
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} | [] | closed | false | null | [] | null | 2 | 2020-12-10T12:13:21 | 2020-12-14T15:00:46 | 2020-12-14T10:31:24 | CONTRIBUTOR | null | I addressed the comments on the PR1318 | {
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https://api.github.com/repos/huggingface/datasets/issues/1452 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1452/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1452/comments | https://api.github.com/repos/huggingface/datasets/issues/1452/events | https://github.com/huggingface/datasets/issues/1452 | 761,104,924 | MDU6SXNzdWU3NjExMDQ5MjQ= | 1,452 | SNLI dataset contains labels with value -1 | {
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} | [] | closed | false | null | [] | null | 2 | 2020-12-10T10:16:55 | 2020-12-10T17:49:55 | 2020-12-10T17:49:55 | NONE | null | ```
import datasets
nli_data = datasets.load_dataset("snli")
train_data = nli_data['train']
train_labels = train_data['label']
label_set = set(train_labels)
print(label_set)
```
**Output:**
`{0, 1, 2, -1}` | {
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} | [] | closed | false | null | [] | null | 0 | 2020-12-10T10:14:20 | 2020-12-11T16:50:09 | 2020-12-11T16:50:09 | CONTRIBUTOR | null | ECDC-TM homepage: https://ec.europa.eu/jrc/en/language-technologies/ecdc-translation-memory | {
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https://api.github.com/repos/huggingface/datasets/issues/1450 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1450/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1450/comments | https://api.github.com/repos/huggingface/datasets/issues/1450/events | https://github.com/huggingface/datasets/pull/1450 | 761,102,429 | MDExOlB1bGxSZXF1ZXN0NTM1ODIwNjg0 | 1,450 | Fix version in bible_para | {
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https://api.github.com/repos/huggingface/datasets/issues/1449 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1449/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1449/comments | https://api.github.com/repos/huggingface/datasets/issues/1449/events | https://github.com/huggingface/datasets/pull/1449 | 761,083,210 | MDExOlB1bGxSZXF1ZXN0NTM1ODA0MzEy | 1,449 | add W&I + LOCNESS dataset (BEA-2019 workshop shared task on GEC) [PROPER] | {
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} | [] | closed | false | null | [] | null | 2 | 2020-12-10T09:51:08 | 2020-12-11T17:07:46 | 2020-12-11T17:07:46 | CONTRIBUTOR | null | - **Name:** W&I + LOCNESS dataset (from the BEA-2019 workshop shared task on GEC)
- **Description:** https://www.cl.cam.ac.uk/research/nl/bea2019st/#data
- **Paper:** https://www.aclweb.org/anthology/W19-4406/
- **Motivation:** This is a recent dataset (actually two in one) for grammatical error correction and is used for benchmarking in this field of NLP.
### Checkbox
- [x] Create the dataset script `/datasets/my_dataset/my_dataset.py` using the template
- [x] Fill the `_DESCRIPTION` and `_CITATION` variables
- [x] Implement `_infos()`, `_split_generators()` and `_generate_examples()`
- [x] Make sure that the `BUILDER_CONFIGS` class attribute is filled with the different configurations of the dataset and that the `BUILDER_CONFIG_CLASS` is specified if there is a custom config class.
- [x] Generate the metadata file `dataset_infos.json` for all configurations
- [x] Generate the dummy data `dummy_data.zip` files to have the dataset script tested and that they don't weigh too much (<50KB)
- [x] Add the dataset card `README.md` using the template : fill the tags and the various paragraphs
- [x] Both tests for the real data and the dummy data pass.
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} | [] | closed | false | null | [] | null | 0 | 2020-12-10T09:48:02 | 2020-12-11T16:21:27 | 2020-12-11T16:21:27 | CONTRIBUTOR | null | Thai Toxicity Tweet Corpus contains 3,300 tweets (506 tweets with texts missing) annotated by humans with guidelines including a 44-word dictionary. The author obtained 2,027 and 1,273 toxic and non-toxic tweets, respectively; these were labeled by three annotators. The result of corpus analysis indicates that tweets that include toxic words are not always toxic. Further, it is more likely that a tweet is toxic, if it contains toxic words indicating their original meaning. Moreover, disagreements in annotation are primarily because of sarcasm, unclear existing target, and word sense ambiguity.
Notes from data cleaner: The data is included into [huggingface/datasets](https://www.github.com/huggingface/datasets) in Dec 2020. By this time, 506 of the tweets are not available publicly anymore. We denote these by `TWEET_NOT_FOUND` in `tweet_text`.
Processing can be found at [this PR](https://github.com/tmu-nlp/ThaiToxicityTweetCorpus/pull/1). | {
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} | [] | closed | false | null | [] | null | 1 | 2020-12-10T09:30:59 | 2020-12-10T12:18:47 | 2020-12-10T09:31:14 | MEMBER | null | Update step-by-step guide for windows to give an alternative to `make style`. | {
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} | [] | closed | false | null | [] | null | 2 | 2020-12-10T09:14:47 | 2020-12-15T17:41:14 | 2020-12-15T17:41:14 | NONE | null | ```py
!pip install datasets
import datasets as ds
corpus = ds.load_dataset('large_spanish_corpus')
```
gives the error
> FileNotFoundError: Couldn't find file locally at large_spanish_corpus/large_spanish_corpus.py, or remotely at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/large_spanish_corpus/large_spanish_corpus.py or https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/large_spanish_corpus/large_spanish_corpus.py
not just `large_spanish_corpus`, `zest` too, but `squad` is available.
this was using colab and localy | {
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} | [] | closed | false | null | [] | null | 0 | 2020-12-10T08:32:07 | 2020-12-17T09:59:43 | 2020-12-17T09:59:43 | MEMBER | null | While I was adding one XML dataset, I noticed that all the dataset was loaded in memory during the dummy data generation process (using nearly all my laptop RAM).
Looking at the code, I have found that the origin is the use of `ET.parse()`. This method loads **all the file content in memory**.
In order to fix this, I have refactorized the code and use `ET.iterparse()` instead, which **parses the file content incrementally**.
I have also implemented a test. | {
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} | [] | closed | false | null | [] | null | 2 | 2020-12-10T07:04:17 | 2020-12-13T05:22:00 | 2020-12-12T05:55:43 | CONTRIBUTOR | null | This PR adds a dataset of 200k English plaintext Jokes from three sources: Reddit, Stupidstuff, and Wocka.
Link: https://github.com/taivop/joke-dataset
This is my second PR.
First was: [#1269 ](https://github.com/huggingface/datasets/pull/1269) | {
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} | [] | closed | false | null | [] | null | 0 | 2020-12-10T06:57:01 | 2020-12-11T15:22:53 | 2020-12-11T15:22:53 | CONTRIBUTOR | null | 1k-10k -> 1k-1M
3 separate configs are available with min. 1K and max. 211.3k examples | {
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Repo: https://github.com/kelvin-jiang/FreebaseQA
Paper: https://www.aclweb.org/anthology/N19-1028.pdf
## TODO: create dummy data
Error encountered when running `python datasets-cli dummy_data datasets/freebase_qa --auto_generate`
```
f"Couldn't parse columns {list(json_data.keys())}. "
ValueError: Couldn't parse columns ['Dataset', 'Version', 'Questions']. Maybe specify which json field must be used to read the data with --json_field <my_field>.
```
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} | [] | closed | false | null | [] | null | 2 | 2020-12-10T01:44:47 | 2020-12-14T13:51:05 | 2020-12-14T13:51:04 | CONTRIBUTOR | null | This is my first dataset to be added to HF. | {
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} | [] | closed | false | null | [] | null | 2 | 2020-12-09T22:05:42 | 2020-12-17T18:13:40 | 2020-12-17T18:13:40 | NONE | null | Hello! I am trying to load single csv file with two columns: ('label': str, 'text' str), where is label is str of two possible classes.
Below steps are similar with [this notebook](https://colab.research.google.com/drive/1-JIJlao4dI-Ilww_NnTc0rxtp-ymgDgM?usp=sharing), where bert model and tokenizer are used to classify lmdb loaded dataset. Only one difference it is the dataset loaded from .csv file.
Here is how I load it:
```python
data_path = 'data.csv'
data = pd.read_csv(data_path)
# process class name to indices
classes = ['neg', 'pos']
class_to_idx = { cl: i for i, cl in enumerate(classes) }
# now data is like {'label': int, 'text' str}
data['label'] = data['label'].apply(lambda x: class_to_idx[x])
# load dataset and map it with defined `tokenize` function
features = Features({
target: ClassLabel(num_classes=2, names=['neg', 'pos'], names_file=None, id=None),
feature: Value(dtype='string', id=None),
})
dataset = Dataset.from_pandas(data, features=features)
dataset.map(tokenize, batched=True, batch_size=len(dataset))
```
It ruins on the last line with following error:
```
---------------------------------------------------------------------------
AssertionError Traceback (most recent call last)
<ipython-input-112-32b6275ce418> in <module>()
9 })
10 dataset = Dataset.from_pandas(data, features=features)
---> 11 dataset.map(tokenizer, batched=True, batch_size=len(dataset))
2 frames
/usr/local/lib/python3.6/dist-packages/datasets/arrow_dataset.py in map(self, function, with_indices, input_columns, batched, batch_size, drop_last_batch, remove_columns, keep_in_memory, load_from_cache_file, cache_file_name, writer_batch_size, features, disable_nullable, fn_kwargs, num_proc, suffix_template, new_fingerprint)
1237 test_inputs = self[:2] if batched else self[0]
1238 test_indices = [0, 1] if batched else 0
-> 1239 update_data = does_function_return_dict(test_inputs, test_indices)
1240 logger.info("Testing finished, running the mapping function on the dataset")
1241
/usr/local/lib/python3.6/dist-packages/datasets/arrow_dataset.py in does_function_return_dict(inputs, indices)
1208 fn_args = [inputs] if input_columns is None else [inputs[col] for col in input_columns]
1209 processed_inputs = (
-> 1210 function(*fn_args, indices, **fn_kwargs) if with_indices else function(*fn_args, **fn_kwargs)
1211 )
1212 does_return_dict = isinstance(processed_inputs, Mapping)
/usr/local/lib/python3.6/dist-packages/transformers/tokenization_utils_base.py in __call__(self, text, text_pair, add_special_tokens, padding, truncation, max_length, stride, is_split_into_words, pad_to_multiple_of, return_tensors, return_token_type_ids, return_attention_mask, return_overflowing_tokens, return_special_tokens_mask, return_offsets_mapping, return_length, verbose, **kwargs)
2281 )
2282 ), (
-> 2283 "text input must of type `str` (single example), `List[str]` (batch or single pretokenized example) "
2284 "or `List[List[str]]` (batch of pretokenized examples)."
2285 )
AssertionError: text input must of type `str` (single example), `List[str]` (batch or single pretokenized example) or `List[List[str]]` (batch of pretokenized examples).
```
which I think is not expected. I also tried the same steps using `Dataset.from_csv` which resulted in the same error.
For reproducing this, I used [this dataset from kaggle](https://www.kaggle.com/team-ai/spam-text-message-classification) | {
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} | [] | closed | false | null | [] | null | 1 | 2020-12-09T21:54:29 | 2020-12-11T13:34:04 | 2020-12-11T13:34:04 | CONTRIBUTOR | null | Contains loading script as well as dataset card including YAML tags. | {
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} | [] | closed | false | null | [] | null | 3 | 2020-12-09T21:08:33 | 2020-12-11T14:02:31 | 2020-12-11T14:02:31 | CONTRIBUTOR | null | This PR adds the Turkish News Categories Dataset (270K) dataset which is a text classification dataset by me and @yavuzKomecoglu. Turkish news dataset consisting of **273601 news** in **17 categories**, compiled from printed media and news websites between 2010 and 2017 by the [Interpress](https://www.interpress.com/) media monitoring company.
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} | [] | closed | false | null | [] | null | 1 | 2020-12-09T21:06:07 | 2020-12-17T09:40:56 | 2020-12-17T09:40:56 | CONTRIBUTOR | null | Data loading script and dataset card for Dialectal Arabic Resources dataset.
Fixed git issues from PR #976 | {
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} | [] | closed | false | null | [] | null | 0 | 2020-12-09T20:38:35 | 2020-12-11T11:23:31 | 2020-12-11T11:23:31 | CONTRIBUTOR | null | Add Shrinked Turkish NER from [Kaggle](https://www.kaggle.com/behcetsenturk/shrinked-twnertc-turkish-ner-data-by-kuzgunlar). | {
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But I'm having a hard time generating dummy data since the original dataset extion is `.arff` and the [_create_dummy_data function](https://github.com/huggingface/datasets/blob/a4aeaf911240057286a01bff1b1d75a89aedd57b/src/datasets/commands/dummy_data.py#L185) doesn't allow it. | {
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I'll make a new PR. | {
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https://arxiv.org/abs/2011.03088 | {
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link: https://huggingface.co/datasets/card-creator/ | {
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> Couldn't find file locally at blah/blah.py, or remotely at https://raw.githubusercontent.com/huggingface/datasets/1.1/metrics/blah/blah.py or https://s3.amazonaws.com/datasets.huggingface.co/datasets/met
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If the dataset was added recently, you may need to to pass script_version="master" to find the loading script on the master branch. | {
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https://sites.google.com/view/felipe-soares/datasets#h.p_92uSCyAjWSRB | {
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} | [] | open | false | null | [] | null | 7 | 2020-12-09T10:59:59 | 2022-07-06T15:19:47 | null | MEMBER | null | When passed `--cache_dir` arg:
```shell
python datasets-cli test datasets/<my-dataset-folder> --save_infos --all_configs --cache_dir <my-cache-dir>
```
it is not used for caching the modules, which are cached in the default location at `.cache/huggingface/modules`.
With this fix, the modules will be cached at `<my-cache-dir>/modules`. | {
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} | [] | closed | false | null | [] | null | 4 | 2020-12-09T10:53:09 | 2020-12-11T13:30:59 | 2020-12-11T13:30:59 | CONTRIBUTOR | null | An update of #309. | {
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Testing with dummy data is not working (the file is said to not exist). Sorry for the incomplete PR. | {
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} | [] | closed | false | null | [] | null | 2 | 2020-12-09T10:06:33 | 2020-12-10T15:37:56 | 2020-12-10T15:37:56 | CONTRIBUTOR | null | # MKQA: Multilingual Knowledge Questions & Answers Dataset
Adding the [MKQA](https://github.com/apple/ml-mkqa) dataset as part of the sprint 🎉
There is no official data splits so I added just a `train` split.
differently from the original:
- answer:type field is a ClassLabel (I thought it might be possible to train on this as a label for categorizing questions)
- answer:entity field has a default value of empty string '' (since this key is not available for all in original)
- answer:alias has default value of []
- [x] All tests passed
- [x] Added dummy data
- [x] Added data card (as much as I could)
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Dataset website: https://yale-lily.github.io/spider
Paper link: https://www.aclweb.org/anthology/D18-1425/ | {
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} | [] | closed | false | null | [] | null | 10 | 2020-12-09T05:52:34 | 2020-12-15T18:12:56 | 2020-12-15T18:12:56 | CONTRIBUTOR | null | This PR adds a new dataset of YouTube captions, error and corrections. This dataset was created in just the last week, as inspired by this sprint! | {
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} | [] | closed | false | null | [] | null | 5 | 2020-12-09T04:59:51 | 2020-12-21T14:48:21 | 2020-12-21T14:48:21 | NONE | null | This PR adds the StackOverflow StackSample dataset from Kaggle: https://www.kaggle.com/stackoverflow/stacksample
Ran through all of the steps. However, since my dataset requires manually downloading the data, I was unable to run the pytest on the real dataset (the dummy data pytest passed). | {
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https://api.github.com/repos/huggingface/datasets/issues/1355 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1355/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1355/comments | https://api.github.com/repos/huggingface/datasets/issues/1355/events | https://github.com/huggingface/datasets/pull/1355 | 759,994,208 | MDExOlB1bGxSZXF1ZXN0NTM0ODk3NzQw | 1,355 | Addition of py_ast dataset | {
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} | [] | closed | false | null | [] | null | 0 | 2020-12-09T04:59:17 | 2020-12-09T16:19:49 | 2020-12-09T16:19:48 | CONTRIBUTOR | null | @lhoestq as discussed in PR #1195 | {
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