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https://api.github.com/repos/huggingface/datasets/issues/352 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/352/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/352/comments | https://api.github.com/repos/huggingface/datasets/issues/352/events | https://github.com/huggingface/datasets/pull/352 | 653,128,883 | MDExOlB1bGxSZXF1ZXN0NDQ2MTA1Mjky | 352 | π[BugFix]fix seqeval | {
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"I think this is good but can you detail a bit the behavior before and after your fix?",
"examples:\r\n\r\ninput: `['B', 'I', 'I', 'O', 'B', 'I']`\r\nbefore: `[('B', 0, 0), ('I', 1, 2), ('B', 4, 4), ('I', 5, 5)]`\r\nafter: `[('_', 0, 2), ('_', 4, 5)]`\r\n\r\ninput: `['B-ARGM-LOC', 'I-ARGM-LOC', 'I-ARGM-LOC', 'O',... | 1,594,199,532,000 | 1,594,888,006,000 | 1,594,888,006,000 | CONTRIBUTOR | null | Fix seqeval process labels such as 'B', 'B-ARGM-LOC' | {
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Usage:
```python
from nlp import load_dataset
dset = load_dataset("pandas", data_files="df.pkl")["train"]
``` | {
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- `from_pandas()` to create a dataset from a pandas dataframe
- `from_dict()` to create a dataset from a dictionary (keys = columns)
It uses the `pa.Table.from_pandas` and `pa.Table.from_pydict` funcitons to do so.
It is also possible to specify the features types v... | {
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"Thank you so much for working on this! This is awesome!\r\n\r\nHow much would it help you if we would remove the manual request?\r\n\r\nWe are naturally interested in getting some broad idea of how many people and who are using our dataset. But if you consider hosting the dataset yourself, I would rather remove th... | 1,594,119,997,000 | 1,594,154,847,000 | 1,594,133,831,000 | CONTRIBUTOR | null | Adding the hyperpartisan news detection dataset from PAN. This contains news article text, labelled with whether they're hyper-partisan and why kinds of biases they display.
Implementation notes:
- As with many PAN tasks, the data is hosted on [Zenodo](https://zenodo.org/record/1489920) and must be requested before... | {
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"@pjox I think the tests don't pass because you haven't provided any dummy data (`dummy_data.zip`).\r\n\r\n ",
"> @pjox I think the tests don't pass because you haven't provided any dummy data (`dummy_data.zip`).\r\n\r\nBut can I do the dummy data without running `python nlp-cli test datasets/<your-dataset-folder... | 1,594,113,727,000 | 1,620,079,628,000 | 1,612,865,959,000 | CONTRIBUTOR | null | I don't know if tests pass, when I run them it tries to download the whole corpus which is around 3.5TB compressed and I don't have that kind of space. I'll really need some help with it π
Thanks! | {
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"This is probably a Windows issue, we need to specify the encoding when `load_dataset()` reads the original CSV file.\r\nTry to find the `open()` statement called by `load_dataset()` and add an `encoding='utf-8'` parameter.\r\nSee issues #242 and #307 ",
"It should be in `xtreme.py:L755`:\r\n```python\r\n ... | 1,594,109,663,000 | 1,599,490,305,000 | 1,599,490,305,000 | CONTRIBUTOR | null | 
I guess the error is related to python source encoding issue that my PC is trying to decode the source code with wrong encoding-decoding tools, perhaps :
https://www.python.org/dev/peps/pep-0263/
I gues... | {
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"I've tried it and am getting the same error as you.\r\n\r\nYou could use the text files rather than the pickle:\r\n```\r\nhttps://www.dropbox.com/s/ikkqxfdbdec3fuj/test.txt\r\nhttps://www.dropbox.com/s/1pzkadrvffbqw6o/train.txt\r\nhttps://www.dropbox.com/s/2mzialpsgf9k5l3/val.txt\r\n```\r\n\r\nThen you would get a... | 1,594,103,741,000 | 1,619,162,023,000 | 1,594,651,178,000 | MEMBER | null | Hello π€ team!
I am trying to add an emotion classification dataset ([link](https://github.com/dair-ai/emotion_dataset)) to `nlp` but I am a bit stuck about what I should do when the URL for the dataset is not a ZIP file, but just a pickled `pandas.DataFrame` (see [here](https://www.dropbox.com/s/607ptdakxuh5i4s/me... | {
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"Hi @saverymax ! For licensing reasons, the original team was unable to release pre-processed CommonCrawl documents. Instead, they provided a script to re-create them from a CommonCrawl dump, but it unfortunately requires access to a medium-large size cluster:\r\nhttps://github.com/facebookresearch/ELI5#downloading... | 1,594,062,853,000 | 1,603,813,125,000 | 1,603,813,125,000 | NONE | null | I was attempting to use the ELI5 dataset, when I realized that huggingface does not provide the supporting documents (the source documents from the common crawl). Without the supporting documents, this makes the dataset about as useful for my project as a block of cheese, or some other more apt metaphor. According to ... | {
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"Could you rebase from master just to make sure we won't break anything for `fever` pls @mariamabarham ?"
] | 1,594,038,196,000 | 1,594,889,896,000 | 1,594,889,896,000 | CONTRIBUTOR | null | This PR adds the Search QA dataset used in **SearchQA: A New Q&A Dataset Augmented with Context from a Search Engine**. The dataset has the following config name:
- raw_jeopardy: raw data
- train_test_val: which is the splitted version
#336 | {
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However I noticed that it was not possible to do `dset.set_format("tensorflow")` on datasets with nested features like `squad`. I fixed that using a nested map operations to convert features to `tf.ragged.constant`.
I also added ... | {
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"`dataset.column_names` are being updated but `dataset.features` aren't indeed..."
] | 1,594,022,603,000 | 1,595,499,316,000 | 1,595,499,316,000 | MEMBER | null | `dataset.map()` can change the schema and column names.
We should update the features in this case (with what is possible to infer). | {
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#336 | {
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"Thanks @brainshawn for this update"
] | 1,593,775,399,000 | 1,593,779,630,000 | 1,593,779,630,000 | CONTRIBUTOR | null | Make the dataset name consistent with in the paper: Compositional Freebase Question => Compositional Freebase Questions. | {
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"Really cool @jarednielsen !\r\nDo you think we can make it work with dataset with nested features like `squad` ?\r\n\r\nI just did a PR to fix `.set_format` for datasets with nested features, but as soon as it's merged we could try to make the conversion work on a dataset like `squad`.",
"For datasets with neste... | 1,593,717,987,000 | 1,595,409,372,000 | 1,595,409,372,000 | CONTRIBUTOR | null | Fixes https://github.com/huggingface/nlp/issues/337
Some design decisions:
- Simplified the function API to not handle sharding. It writes the entire dataset as a single TFRecord file. This simplifies the function logic and users can use other functions (`select`, `shard`, etc) to handle custom sharding or splitt... | {
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```python
# use these existing methods
ds = load_dataset("wikitext", "wik... | {
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Namely, it would be really nice to add:
- WebQuestions (Berant et al., 2013) [done]
- CuratedTrec (Baudis et al. 2015) [not open-source]
- MS-MARCO (NGuyen et al. 2016) [done]
- SearchQA (Dunn et al.... | {
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"I fixed the issues that you pointed out, re-run all the test and pushed the fixed code :-)",
"```\r\n=================================== FAILURES ===================================\r\n___________________ AWSDatasetTest.test_load_dataset_pandas ____________________\r\n\r\nself = <tests.test_dataset_common.AWSDat... | 1,593,680,621,000 | 1,594,800,127,000 | 1,594,800,127,000 | CONTRIBUTOR | null | {
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"Great, done!"
] | 1,593,669,919,000 | 1,594,038,936,000 | 1,594,038,936,000 | CONTRIBUTOR | null | Fixes https://github.com/huggingface/nlp/issues/312 | {
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"Good catch :)\r\nI think there is another occurence that needs to be fixed in the second gist (line 4924 of the notebook file):\r\n```python\r\nbleu = nlp.load_metric(...)\r\n```",
"Was fixed in e16f79b5f7fc12a6a30c777722be46897a272e6f\r\nClosing it."
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"The two configurations don't have the same sizes, I may change that so that they both have 21015300 examples for convenience, even though it's supposed to have 21015324 examples in total.\r\n\r\nOne configuration only has 21015300 examples because it seems that the embeddings of the last 24 examples are missing.",... | 1,593,623,520,000 | 1,594,038,077,000 | 1,594,038,076,000 | MEMBER | null | Presented in the [Dense Passage Retrieval paper](https://arxiv.org/pdf/2004.04906.pdf), this dataset consists in 21M passages from the english wikipedia along with their 768-dim embeddings computed using DPR's context encoder.
Note on the implementation:
- There are two configs: with and without the embeddings (73G... | {
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"I couldn't reproduce on my side.\r\nIt looks like you were not able to generate all the examples, and you have the problem for each split train-test-validation.\r\nCould you try to enable logging, try again and send the logs ?\r\n```python\r\nimport logging\r\nlogging.basicConfig(level=logging.INFO)\r\n```",
"he... | 1,593,555,693,000 | 1,594,299,820,000 | 1,594,299,820,000 | CONTRIBUTOR | null | ```
>>> import nlp
>>> nlp.load_dataset('cnn_dailymail', '3.0.0')
Downloading and preparing dataset cnn_dailymail/3.0.0 (download: 558.32 MiB, generated: 1.26 GiB, total: 1.81 GiB) to /u/jm8wx/.cache/huggingface/datasets/cnn_dailymail/3.0.0/3.0.0...
Traceback (most recent call last):
File "<stdin>", line 1, in... | {
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- There are 2 separate versions of the training set - *annotated* and *distant*. Instead of `nlp.Split.Train` I've used the splits `"train_annotated"` and `"train_distant"` to ... | {
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"Hi, can you give details on your environment/os/packages versions/etc?",
"Environment is Ubuntu 18.04, Python 3.7.5, nlp==0.3.0, filelock=3.0.12.\r\n\r\nThe external volume is Amazon FSx for Lustre, and it by default creates files with limited permissions. My working theory is that FileLock creates a lockfile th... | 1,593,546,331,000 | 1,593,586,558,000 | 1,593,552,786,000 | CONTRIBUTOR | null | I'm downloading a dataset successfully with
`load_dataset("wikitext", "wikitext-2-raw-v1")`
But when I attempt to cache it on an external volume, it hangs indefinitely:
`load_dataset("wikitext", "wikitext-2-raw-v1", cache_dir="/fsx") # /fsx is an external volume mount`
The filesystem when hanging looks like thi... | {
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"To be able to generate the Arrow dataset you need to either use our csv or json utilities `load_dataset(\"json\", data_files=my_json_files)` OR write your own custom dataset script (you can find some inspiration from the [squad](https://github.com/huggingface/nlp/blob/master/datasets/squad/squad.py) script for exa... | 1,593,535,373,000 | 1,594,071,839,000 | 1,594,071,839,000 | NONE | null | We have a multi-task learning model training I'm trying to convert to using the Arrow-based nlp dataset.
We're currently training a custom TensorFlow model but the nlp paradigm should be a bridge for us to be able to use the wealth of pre-trained models in Transformers.
Our preprocessing flow parses raw text and... | {
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"I'm pretty sure you can get some inspiration from the squad_v2 script. It looks like the dataset is quite big so it will take some time for the users to generate it, but it should be reasonable.\r\n\r\nAlso you are saying that you are still making the dataset grow in size right ?\r\nIt's probably good practice to ... | 1,593,519,539,000 | 1,594,285,310,000 | 1,594,285,310,000 | NONE | null | At the moment we are building an large question answering dataset and think about sharing it with the huggingface community.
Caused the computing power we splitted it into multiple tiles, but they are all in the same format.
Right now the most important facts about are this:
- Contexts: 1.047.671
- questions: 1.677... | {
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"Very cool to have this dataset, thank you for adding it :)"
] | 1,593,457,876,000 | 1,593,536,851,000 | 1,593,536,851,000 | CONTRIBUTOR | null | This PR adds the four new variants of the SQuAD dataset used in [The Effect of Natural Distribution Shift on Question Answering Models](https://arxiv.org/abs/2004.14444) to facilitate evaluating model robustness to distribution shift. | {
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"The glue metric for cola is a metric for classification. It expects label ids as integers as inputs.",
"I want to evaluate a sentence pair whether they are semantically equivalent, so I used MRPC and it gives the same error, does that mean we have to encode the sentences and parse as input?\r\n\r\nusing BertToke... | 1,593,449,628,000 | 1,594,286,014,000 | 1,594,286,014,000 | NONE | null | I was trying glue score along with other metrics here. But glue gives me this error;
```
import nlp
glue_metric = nlp.load_metric('glue',name="cola")
glue_score = glue_metric.compute(predictions, references)
```
```
---------------------------------------------------------------------------
--------------... | {
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"Sorry for the long diff, everything after the imports comes from `black` for code quality :/ ",
" I think it's fine and I can't think of another way to make the import work anyways.\r\n\r\nMaybe we can have the `sys.path` behavior inside `prepare_module` instead ? Currently it seems to come out of nowhere in the... | 1,593,449,161,000 | 1,596,117,623,000 | 1,596,117,623,000 | MEMBER | null | This fixes the `coval.py` metric so that imports within the downloaded module work correctly. We can use a similar trick to add the BLEURT metric (@ankparikh)
@thomwolf not sure how you feel about adding to the `PYTHONPATH` from the script. This is the only way I could make it work with my understanding of `importli... | {
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```python
my_examples = dataset[0:10]
print(type(my_examples))
# >>> dict
print(my_examples["my_column"][0]
# >>> this is the first element of the colum... | {
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"It looks like it comes from `mwparserfromhell`.\r\n\r\nWould it be possible to get the bad `section` that causes this issue ? The `section` string is from `datasets/wikipedia.py:L548` ? You could just add a `try` statement and print the section if the line `section_text.append(section.strip_code().strip())` crashe... | 1,593,429,043,000 | 1,595,521,714,000 | null | NONE | null | Hi,
I am trying to download some wikipedia data but I got this error for spanish "es" (but there are maybe some others languages which have the same error I haven't tried all of them ).
`ERROR:root:mwparserfromhell ParseError: This is a bug and should be reported. Info: C tokenizer exited with non-empty token sta... | {
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"I wonder if this means downloading failed? That corpus has a really slow server.",
"This dataset seems to have a decoding problem that results in inconsistencies in the number of generated examples.\r\nSee #215.\r\nThat's why we end up with a `NonMatchingSplitsSizesError `."
] | 1,593,416,195,000 | 1,593,441,882,000 | 1,593,441,882,000 | CONTRIBUTOR | null | Selecting `blog_authorship_corpus` in the nlp viewer throws the following error:
```
NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='train', num_bytes=610252351, num_examples=532812, dataset_name='blog_authorship_corpus'), 'recorded': SplitInfo(name='train', num_bytes=614706451, num_examples=535568, dat... | {
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"Oh yes, this is a backward compatibility feature with tensorflow_dataset in which a `Sequence` or `dict` is converted in a `dict` of `lists`, unfortunately it is not very intuitive, see here: https://github.com/huggingface/nlp/blob/master/src/nlp/features.py#L409\r\n\r\nTo avoid this behavior, you can just define ... | 1,593,301,517,000 | 1,593,771,720,000 | 1,593,771,720,000 | CONTRIBUTOR | null | Am pretty much finished [adding a dataset](https://github.com/ghomasHudson/nlp/blob/DocRED/datasets/docred/docred.py) for [DocRED](https://github.com/thunlp/DocRED), but am getting an error when trying to add a nested `nlp.features.sequence(nlp.features.sequence({key:value,...}))`.
The original data is in this form... | {
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"It's definitely going in the right direction ! Thanks for giving it a try\r\n\r\nI really like the API.\r\nIMO it's fine right now if we don't have all the dataset transforms (map, filter, etc.) as it can be done before building the multitask dataset, but it will be important to have them in the end.\r\nAll the fo... | 1,593,264,449,000 | 1,638,487,489,000 | null | CONTRIBUTOR | null | Following our discussion in #217, I've implemented a first working version of `MultiDataset`.
There's a function `build_multitask()` which takes either individual `nlp.Dataset`s or `dicts` of splits and constructs `MultiDataset`(s). I've added a notebook with example usage.
I've implemented many of the `nlp.Datas... | {
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"For one dataset you can have different configurations that each have their own `nlp.Features`.\r\nWe imagine having one configuration per subtask for example.\r\nThey are loaded with `nlp.load_dataset(\"my_dataset\", \"my_config\")`.\r\n\r\nFor example the `glue` dataset has many configurations. It is a bit differ... | 1,593,213,259,000 | 1,603,813,012,000 | 1,603,813,012,000 | NONE | null | I intent to add the datasets of the MT Quality Estimation shared tasks to `nlp`. However, they have different subtasks -- such as word-level, sentence-level and document-level quality estimation, each of which having different language pairs, and some of the data reused in different subtasks.
For example, in [QE 201... | {
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"Thanks @jxmorris12 for adding this adding. \r\nCan you please add a small description of the PR?"
] | 1,593,187,918,000 | 1,593,511,088,000 | 1,593,505,915,000 | CONTRIBUTOR | null | adds support for the AG-News topic classification dataset | {
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"Update: I think I've found a solution.\r\n\r\n```python\r\noutput_types = {\"input_ids\": tf.int64, \"token_type_ids\": tf.int64, \"attention_mask\": tf.int64}\r\ndef train_dataset_gen():\r\n for i in range(len(train_dataset)):\r\n yield train_dataset[i]\r\ntf_dataset = tf.data.Dataset.from_generator(tra... | 1,593,124,220,000 | 1,603,813,097,000 | null | CONTRIBUTOR | null | I'm training on large datasets such as Wikipedia and BookCorpus. Following the instructions in [the tutorial notebook](https://colab.research.google.com/github/huggingface/nlp/blob/master/notebooks/Overview.ipynb), I see the following recommended for TensorFlow:
```python
train_tf_dataset = train_tf_dataset.filter(... | {
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"Thank you BatJeti! The storm-joker, aka the typo, finally got caught!"
] | 1,593,081,959,000 | 1,593,161,201,000 | 1,593,089,039,000 | CONTRIBUTOR | null | An instance of "independantly" was changed to "independently". That's all. | {
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"Looks good to me"
] | 1,593,076,922,000 | 1,593,505,691,000 | 1,593,505,691,000 | CONTRIBUTOR | null | Adding the [Modified Winograd Schema Challenge](https://github.com/salesforce/decaNLP/blob/master/local_data/schema.txt) dataset which formed part of the [decaNLP](http://decanlp.com/) benchmark. Not sure how much use people would find for it it outside of the benchmark, but it is general purpose.
Code is heavily bo... | {
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"Hi Jared,\r\nInteresting, thanks for raising this question. You can also do that after loading with `dataset.select()` or `dataset.filter()` which let you keep only a specific subset of rows in a dataset.\r\nWhat is your use-case for sharding?",
"Thanks for the pointer to those functions! It's still a little mor... | 1,593,038,913,000 | 1,594,038,936,000 | 1,594,038,936,000 | CONTRIBUTOR | null | Currently, to shard a dataset into 10 pieces on different ranks, you can run
```python
rank = 3 # for example
size = 10
dataset = nlp.load_dataset('wikitext', 'wikitext-2-raw-v1', split=f"train[{rank*10}%:{(rank+1)*10}%]")
```
However, this breaks down if you have a number of ranks that doesn't divide cleanly... | {
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A common processing step seems to be replacing the `XXX` placeholder with the `subject`. I've left this out as it's something you could easily do with `map`. | {
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"That's great work @ghomasHudson !"
] | 1,593,021,635,000 | 1,593,088,345,000 | 1,593,088,345,000 | CONTRIBUTOR | null | Adding the [WikiSQL](https://github.com/salesforce/WikiSQL) dataset.
Interesting things to note:
- Have copied the function (`_convert_to_human_readable`) which converts the SQL query to a human-readable (string) format as this is what most people will want when actually using this dataset for NLP applications.
- ... | {
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"Does it make sense to download the full stories? I remember attempting to implement this dataset a while ago and ended up with something like:\r\n```python\r\n def _split_generators(self, dl_manager):\r\n \"\"\"Returns SplitGenerators.\"\"\"\r\n\r\n dl_dir = dl_manager.download_and_extract(_DOWNLO... | 1,593,019,578,000 | 1,599,123,730,000 | 1,599,123,729,000 | NONE | null | Test cases for dummy data don't pass
Only contains data for summaries (not whole story) | {
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```python
dataset = nlp.load_dataset('glue', 'mrpc')
```
```python
Downloading and preparing dataset glue/mrpc (download: Unknown size, generated: Unknown size, total: Unknown size) to C:\Users\Python\.cache... | {
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https://api.github.com/repos/huggingface/datasets/issues/306 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/306/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/306/comments | https://api.github.com/repos/huggingface/datasets/issues/306/events | https://github.com/huggingface/datasets/pull/306 | 644,176,078 | MDExOlB1bGxSZXF1ZXN0NDM4ODQ2MTI3 | 306 | add pg19 dataset | {
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"@lucidrains - Thanks a lot for making the PR - PG19 is a super important dataset! Thanks for making it. Many people are asking for PG-19, so it would be great to have that in the library as soon as possible @thomwolf .",
"@mariamabarham yup! around 11GB!",
"I'm looking forward to our first deep learning writte... | 1,592,949,832,000 | 1,594,022,159,000 | 1,594,022,159,000 | CONTRIBUTOR | null | https://github.com/huggingface/nlp/issues/274
Add functioning PG19 dataset with dummy data
`cos_e.py` was just auto-linted by `make style` | {
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Currently however, the code seems to... | {
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Attached [Colab](https://colab.research.google.com/drive/13H0ZgyQ2se0mqJ2yyew0bNEgJuHaJ8H3?usp=sharing) Notebook for problem ... | {
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Therefore it can happen that we try to move files across filesystems.
We were using `os.rename` that doesn't allow that, so I changed some of them to `shutil.move`.
This should fix #301 | {
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"Even more complicating - \r\n\r\nAs I see it, datasets can have \"addons\".\r\nFor example, the WebNLG dataset is a dataset for data-to-text. However, a work of mine and other works enriched this dataset with text plans / underlying text structures. In that case, I see a need to load the dataset \"WebNLG\" with \"... | 1,592,924,020,000 | 1,606,303,533,000 | 1,606,303,533,000 | CONTRIBUTOR | null | An emerging field in NLP is SLP - sign language processing.
I was wondering about adding datasets here, specifically because it's shaping up to be large and easily usable.
The metrics for sign language to text translation are the same.
So, what do you think about (me, or others) adding datasets here?
An exa... | {
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"Whoops didn't mean to close this one.\r\nI did some changes, could you try to run it from the master branch ?",
"Now it works, thanks!"
] | 1,592,911,904,000 | 1,592,982,307,000 | 1,592,982,307,000 | NONE | null | First of all thank you for a super handy library! I'd like to download large files to a specific drive so I set `cache_dir=my_path`. This works fine with e.g. imdb and squad. But on wikipedia I get an error:
```
nlp.load_dataset('wikipedia', '20200501.de', split = 'train', cache_dir=my_path)
```
```
OSError ... | {
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https://api.github.com/repos/huggingface/datasets/issues/300 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/300/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/300/comments | https://api.github.com/repos/huggingface/datasets/issues/300/events | https://github.com/huggingface/datasets/pull/300 | 643,688,304 | MDExOlB1bGxSZXF1ZXN0NDM4NDQ4Mjk1 | 300 | Fix bertscore references | {
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Moreover I added support for both strings and lists of strings for `references` in `bertscore`, as it is the case in the original code.
Both... | {
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"I guess you can just rebase from master to fix the CI"
] | 1,592,898,366,000 | 1,592,899,846,000 | 1,592,899,844,000 | CONTRIBUTOR | null | This PR removes unwanted `print` statements in some files such as `snli.py` | {
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"Looks very cool! Only looked at it superficially though",
"Alright I think I've checked all your comments, thanks :)\r\n\r\nMoreover I just added a way to serialize faiss indexes.\r\nThis is important because for big datasets the index construction can take some time.\r\n\r\nExamples:\r\n\r\n```python\r\nds = nl... | 1,592,897,583,000 | 1,593,157,844,000 | 1,593,157,843,000 | MEMBER | null | # Better support for Numpy format + Add Indexed Datasets
I was working on adding Indexed Datasets but in the meantime I had to also add more support for Numpy arrays in the lib.
## Better support for Numpy format
New features:
- New fast method to convert Numpy arrays from Arrow structure (up to x100 speed up... | {
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"Thanks for reporting these errors :)\r\n\r\nI can actually see two issues here.\r\n\r\nFirst, datasets like `natural_questions` require apache_beam to be processed. Right now the import is not at the right place so we have this error message. However, even the imports are fixed, the nlp viewer doesn't actually hav... | 1,592,872,722,000 | 1,595,007,786,000 | 1,595,007,786,000 | NONE | null | Selecting `natural_questions` or `newsroom` dataset in the online demo results in an error similar to the following.
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"@jxmorris12 , we use `-1` to label examples for which `gold label` is missing (`gold label = -` in the original dataset). ",
"Thanks @mariamabarham! so the original dataset is missing some labels? That is weird. Is standard practice just to discard those examples training/eval?",
"Yes the original dataset is... | 1,592,868,810,000 | 1,592,923,319,000 | 1,592,923,318,000 | CONTRIBUTOR | null | I'm trying to train a model on the SNLI dataset. Why does it have so many -1 labels?
```
import nlp
from collections import Counter
data = nlp.load_dataset('snli')['train']
print(Counter(data['label']))
Counter({0: 183416, 2: 183187, 1: 182764, -1: 785})
```
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I am the author of `bert_score`. Recently, we received [ an issue ](https://github.com/Tiiiger/bert_score/issues/62) reporting a problem in using `bert_score` from the `nlp` package (also see #238 in this repo). After looking into this, I realized that the problem arises from the format `nlp.Metric` takes inpu... | {
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"I couldn't replicate this issue on my macbook :/\r\nCould you try to play with different encodings in `with open(path, encoding=...) as f` in scientific_papers.py:L108 ?",
"I was able to track down the file causing the problem by adding the following to `scientific_papers.py` (starting at line 116):\r\n\r\n```py... | 1,592,840,815,000 | 1,593,530,710,000 | 1,593,530,710,000 | NONE | null | I am having trouble loading the `"arxiv"` config from the `"scientific_papers"` dataset on MacOS. When I try loading the dataset with:
```python
arxiv = nlp.load_dataset("scientific_papers", "arxiv")
```
I get the following stack trace:
```bash
JSONDecodeError Traceback (most recen... | {
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It should fix the CI that is currently failing. | {
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https://api.github.com/repos/huggingface/datasets/issues/292 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/292/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/292/comments | https://api.github.com/repos/huggingface/datasets/issues/292/events | https://github.com/huggingface/datasets/pull/292 | 642,897,797 | MDExOlB1bGxSZXF1ZXN0NDM3Nzk4NTM2 | 292 | Update metadata for x_stance dataset | {
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"Great! Thanks @jvamvas for these updates.\r\n",
"I have fixed a warning. The remaining test failure is due to an unrelated dataset.",
"We just fixed the other dataset on master. Could you rebase from master and push to rerun the CI ?"
] | 1,592,817,206,000 | 1,592,899,644,000 | 1,592,899,644,000 | CONTRIBUTOR | null | Thank you for featuring the x_stance dataset in your library. This PR updates some metadata:
- Citation: Replace preprint with proceedings
- URL: Use a URL with long-term availability
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"I guess,test failing due to connection error?",
"We just fixed the other dataset on master. Could you rebase from master and push to rerun the CI ?",
"If I'm not wrong this function returns None if no main class was found.\r\nI think it makes things less clear not to have a return at the end of the function.\r... | 1,592,790,055,000 | 1,592,935,078,000 | 1,592,905,022,000 | NONE | null | {
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"It should ne fixed now, thanks for reporting this one :)\r\nIt was an issue on our google storage.\r\n\r\nLet me now if you're still facing this issue.",
"It works now, thanks for prompt help!"
] | 1,592,574,033,000 | 1,592,659,344,000 | 1,592,659,344,000 | NONE | null | Hi, I have a problem with downloading Eli5 dataset. When typing `nlp.load_dataset('eli5')`, I get ConnectionError: Couldn't reach https://storage.googleapis.com/huggingface-nlp/cache/datasets/eli5/LFQA_reddit/1.0.0/explain_like_im_five-train_eli5.arrow
I would appreciate if you could help me with this issue. | {
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"Looks cool!\r\n@mariamabarham can you add a detailed description here what exactly is changed and how the user can load xsum now?",
"And a rebase should solve the conflicts",
"This is a super useful PR :-) @sshleifer - maybe you can take a look at the updated version of xsum if you can use it for your use case... | 1,592,569,712,000 | 1,592,832,446,000 | 1,592,810,407,000 | CONTRIBUTOR | null | This PR makes the following update to the xsum dataset:
- Manual download is not required anymore
- dataset can be loaded as follow: `nlp.load_dataset('xsum')`
**Important**
Instead of using on outdated url to download the data: "https://raw.githubusercontent.com/EdinburghNLP/XSum/master/XSum-Dataset/XSum... | {
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https://api.github.com/repos/huggingface/datasets/issues/288 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/288/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/288/comments | https://api.github.com/repos/huggingface/datasets/issues/288/events | https://github.com/huggingface/datasets/issues/288 | 641,888,610 | MDU6SXNzdWU2NDE4ODg2MTA= | 288 | Error at the first example in README: AttributeError: module 'dill' has no attribute '_dill' | {
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"It looks like the bug comes from `dill`. Which version of `dill` are you using ?",
"Thank you. It is version 0.2.6, which version is better?",
"0.2.6 is three years old now, maybe try a more recent one, e.g. the current 0.3.2 if you can?",
"Thanks guys! I upgraded dill and it works.",
"Awesome"
] | 1,592,564,482,000 | 1,592,730,311,000 | 1,592,730,311,000 | NONE | null | /Users/parasol_tree/anaconda3/lib/python3.6/site-packages/tensorflow/python/framework/dtypes.py:469: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.
_np_qint8 = np.dtype([("qint8", np.int8, 1)])
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The imports were wrong | {
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https://api.github.com/repos/huggingface/datasets/issues/286 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/286/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/286/comments | https://api.github.com/repos/huggingface/datasets/issues/286/events | https://github.com/huggingface/datasets/pull/286 | 641,585,758 | MDExOlB1bGxSZXF1ZXN0NDM2NzkzMjI4 | 286 | Add ANLI dataset. | {
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"Awesome!! Thanks @easonnie.\r\nLet's wait for additional reviews maybe from @lhoestq @patrickvonplaten @jplu"
] | 1,592,519,250,000 | 1,592,828,607,000 | 1,592,828,607,000 | CONTRIBUTOR | null | I completed all the steps in https://github.com/huggingface/nlp/blob/master/CONTRIBUTING.md#how-to-add-a-dataset and push the code for ANLI. Please let me know if there are any errors. | {
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https://api.github.com/repos/huggingface/datasets/issues/285 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/285/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/285/comments | https://api.github.com/repos/huggingface/datasets/issues/285/events | https://github.com/huggingface/datasets/pull/285 | 641,360,702 | MDExOlB1bGxSZXF1ZXN0NDM2NjAyMjk4 | 285 | Consistent formatting of citations | {
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"Circle CI shuold be green :-) "
] | 1,592,497,523,000 | 1,592,813,365,000 | 1,592,813,364,000 | CONTRIBUTOR | null | #283 | {
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https://api.github.com/repos/huggingface/datasets/issues/284 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/284/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/284/comments | https://api.github.com/repos/huggingface/datasets/issues/284/events | https://github.com/huggingface/datasets/pull/284 | 641,337,217 | MDExOlB1bGxSZXF1ZXN0NDM2NTgxODQ2 | 284 | Fix manual download instructions | {
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"Verified that this works, thanks!",
"But I get\r\n```python\r\nConnectionError: Couldn't reach https://s3.amazonaws.com/datasets.huggingface.co/nlp/datasets/./datasets/wmt16/wmt16.py\r\n```\r\nWhen I try from jupyter on brutasse or my mac. (the jupyter server is run from transformers).\r\n\r\n\r\nBoth machines c... | 1,592,495,997,000 | 1,592,555,061,000 | 1,592,555,059,000 | MEMBER | null | This PR replaces the static `DatasetBulider` variable `MANUAL_DOWNLOAD_INSTRUCTIONS` by a property function `manual_download_instructions()`.
Some datasets like XTREME and all WMT need the manual data dir only for a small fraction of the possible configs.
After some brainstorming with @mariamabarham and @lhoestq... | {
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https://api.github.com/repos/huggingface/datasets/issues/283 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/283/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/283/comments | https://api.github.com/repos/huggingface/datasets/issues/283/events | https://github.com/huggingface/datasets/issues/283 | 641,270,439 | MDU6SXNzdWU2NDEyNzA0Mzk= | 283 | Consistent formatting of citations | {
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Can we make it so that they all are proper citations, i.e. parse by the bibtex spec:
https://bibtexparser.readthedocs.io/en/master/ | {
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https://api.github.com/repos/huggingface/datasets/issues/282 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/282/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/282/comments | https://api.github.com/repos/huggingface/datasets/issues/282/events | https://github.com/huggingface/datasets/pull/282 | 641,217,759 | MDExOlB1bGxSZXF1ZXN0NDM2NDgxNzMy | 282 | Update dataset_info from gcs | {
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https://api.github.com/repos/huggingface/datasets/issues/281 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/281/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/281/comments | https://api.github.com/repos/huggingface/datasets/issues/281/events | https://github.com/huggingface/datasets/issues/281 | 641,067,856 | MDU6SXNzdWU2NDEwNjc4NTY= | 281 | Private/sensitive data | {
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"Hi @MFreidank, you should already be able to load a dataset from local sources, indeed. (ping @lhoestq and @jplu)\r\n\r\nWe're also thinking about the ability to host private datasets on a hosted bucket with permission management, but that's further down the road.",
"Hi @MFreidank, it is possible to load a datas... | 1,592,473,647,000 | 1,592,658,912,000 | 1,592,658,912,000 | NONE | null | Hi all,
Thanks for this fantastic library, it makes it very easy to do prototyping for NLP projects interchangeably between TF/Pytorch.
Unfortunately, there is data that cannot easily be shared publicly as it may contain sensitive information.
Is there support/a plan to support such data with NLP, e.g. by readin... | {
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https://api.github.com/repos/huggingface/datasets/issues/280 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/280/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/280/comments | https://api.github.com/repos/huggingface/datasets/issues/280/events | https://github.com/huggingface/datasets/issues/280 | 640,677,615 | MDU6SXNzdWU2NDA2Nzc2MTU= | 280 | Error with SquadV2 Metrics | {
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**squad_metric = nlp.load_metric('squad_v2')**
**This throws me an error.:**
```
ImportError Traceback (most recent call last)
<ipython-input-8-170b6a170555> in <module>
----> 1 squad_metric = nlp.load_metric('squad_v2')
~/env/lib6... | {
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https://api.github.com/repos/huggingface/datasets/issues/279 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/279/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/279/comments | https://api.github.com/repos/huggingface/datasets/issues/279/events | https://github.com/huggingface/datasets/issues/279 | 640,611,692 | MDU6SXNzdWU2NDA2MTE2OTI= | 279 | Dataset Preprocessing Cache with .map() function not working as expected | {
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"When you're processing a dataset with `.map`, it checks whether it has already done this computation using a hash based on the function and the input (using some fancy serialization with `dill`). If you found that it doesn't work as expected in some cases, let us know !\r\n\r\nGiven that, you can still force to re... | 1,592,414,241,000 | 1,625,607,808,000 | 1,618,789,429,000 | NONE | null | I've been having issues with reproducibility when loading and processing datasets with the `.map` function. I was only able to resolve them by clearing all of the cache files on my system.
Is there a way to disable using the cache when processing a dataset? As I make minor processing changes on the same dataset, I ... | {
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"Hi !\r\n\r\nAs you noticed, \"big\" datasets like Wikipedia require apache beam to be processed.\r\nHowever users usually don't have an apache beam runtime available (spark, dataflow, etc.) so our goal for this library is to also make available processed versions of these datasets, so that users can just download ... | 1,592,406,381,000 | 1,592,571,182,000 | 1,592,571,182,000 | NONE | null | Hi, first off let me say thank you for all the awesome work you're doing at Hugging Face across all your projects (NLP, Transformers, Tokenizers) - they're all amazing contributions to us working with NLP models :)
I'm trying to download the German Wikipedia dataset as follows:
```
wiki = nlp.load_dataset("wikip... | {
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https://api.github.com/repos/huggingface/datasets/issues/277 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/277/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/277/comments | https://api.github.com/repos/huggingface/datasets/issues/277/events | https://github.com/huggingface/datasets/issues/277 | 640,163,053 | MDU6SXNzdWU2NDAxNjMwNTM= | 277 | Empty samples in glue/qqp | {
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"We are only wrapping the original dataset.\r\n\r\nMaybe try to ask on the GLUE mailing list or reach out to the original authors?",
"Tanks for the suggestion, I'll try to ask GLUE benchmark.\r\nI'll first close the issue, post the following up here afterwards, and reopen the issue if needed. "
] | 1,592,373,292,000 | 1,592,698,905,000 | 1,592,698,905,000 | CONTRIBUTOR | null | ```
qqp = nlp.load_dataset('glue', 'qqp')
print(qqp['train'][310121])
print(qqp['train'][362225])
```
```
{'question1': 'How can I create an Android app?', 'question2': '', 'label': 0, 'idx': 310137}
{'question1': 'How can I develop android app?', 'question2': '', 'label': 0, 'idx': 362246}
```
Notice that que... | {
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https://api.github.com/repos/huggingface/datasets/issues/276 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/276/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/276/comments | https://api.github.com/repos/huggingface/datasets/issues/276/events | https://github.com/huggingface/datasets/pull/276 | 639,490,858 | MDExOlB1bGxSZXF1ZXN0NDM1MDY5Nzg5 | 276 | Fix metric compute (original_instructions missing) | {
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"Awesome! This is working now:\r\n\r\n```python\r\nimport nlp \r\nseqeval = nlp.load_metric(\"seqeval\") \r\ny_true = [['O', 'O', 'O', 'B-MISC', 'I-MISC', 'I-MISC', 'O'], ['B-PER', 'I-PER', 'O']] \r\ny_pred = [['O', 'O', 'B-MISC', 'I-MISC', 'I-MISC', 'I-MISC', 'O'], ['B-PER', 'I-PER', 'O']] ... | 1,592,297,521,000 | 1,592,466,105,000 | 1,592,466,104,000 | MEMBER | null | When loading arrow data we added in cc8d250 a way to specify the instructions that were used to store them with the loaded dataset.
However metrics load data the same way but don't need instructions (we use one single file).
In this PR I just make `original_instructions` optional when reading files to load a `Datas... | {
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https://api.github.com/repos/huggingface/datasets/issues/275 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/275/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/275/comments | https://api.github.com/repos/huggingface/datasets/issues/275/events | https://github.com/huggingface/datasets/issues/275 | 639,439,052 | MDU6SXNzdWU2Mzk0MzkwNTI= | 275 | NonMatchingChecksumError when loading pubmed dataset | {
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"For some reason the files are not available for unauthenticated users right now (like the download service of this package). Instead of downloading the right files, it downloads the html of the error.\r\nAccording to the error it should be back again in 24h.\r\n\r\n`.
The error is:
```
---------------------------------------------------------------------------
NonMatchingChecksumError Traceback (most recent call last)
<ipython-input-2-7742dea167d0> in <module... | {
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"Sounds good! Do you want to give it a try?",
"Ok, I'll see if I can figure it out tomorrow!",
"Got around to this today, and so far so good, I'm able to download and load pg19 locally. However, I think there may be an issue with the dummy data, and testing in general.\r\n\r\nThe problem lies in the fact that e... | 1,592,254,946,000 | 1,594,049,702,000 | 1,594,049,702,000 | CONTRIBUTOR | null | Hi, and thanks for all your open-sourced work, as always!
I was wondering if you would be open to adding PG-19 to your collection of datasets. https://github.com/deepmind/pg19 It is often used for benchmarking long-range language modeling. | {
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https://api.github.com/repos/huggingface/datasets/issues/273 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/273/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/273/comments | https://api.github.com/repos/huggingface/datasets/issues/273/events | https://github.com/huggingface/datasets/pull/273 | 638,968,054 | MDExOlB1bGxSZXF1ZXN0NDM0NjM0MzU4 | 273 | update cos_e to add cos_e v1.0 | {
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@nazneenrajani | {
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https://api.github.com/repos/huggingface/datasets/issues/271 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/271/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/271/comments | https://api.github.com/repos/huggingface/datasets/issues/271/events | https://github.com/huggingface/datasets/pull/271 | 638,135,754 | MDExOlB1bGxSZXF1ZXN0NDMzOTg3NDkw | 271 | Fix allocinΓ© dataset configuration | {
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"Actually when there is only one configuration, then you don't need to specify the configuration in `load_dataset`. You can run:\r\n```python\r\ndataset = load_dataset('allocine')\r\n```\r\nand it works.\r\n\r\nMaybe we should take that into account in the nlp viewer @srush ?",
"@lhoestq Just to understand the ex... | 1,592,043,130,000 | 1,592,466,081,000 | 1,592,466,080,000 | CONTRIBUTOR | null | This is a patch for #244. According to the [live nlp viewer](url), the AllocinΓ© dataset must be loaded with :
```python
dataset = load_dataset('allocine', 'allocine')
```
This is redundant, as there is only one "dataset configuration", and should only be:
```python
dataset = load_dataset('allocine')
```
This ... | {
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"C4 is too large to be shown in the viewer"
] | 1,592,036,776,000 | 1,603,812,929,000 | 1,603,812,913,000 | NONE | null | I get the following error when I try to view the c4 dataset in [nlpviewer](https://huggingface.co/nlp/viewer/)
```python
ModuleNotFoundError: No module named 'langdetect'
Traceback:
File "/home/sasha/.local/lib/python3.7/site-packages/streamlit/ScriptRunner.py", line 322, in _run_script
exec(code, module.__d... | {
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https://api.github.com/repos/huggingface/datasets/issues/269 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/269/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/269/comments | https://api.github.com/repos/huggingface/datasets/issues/269/events | https://github.com/huggingface/datasets/issues/269 | 638,106,774 | MDU6SXNzdWU2MzgxMDY3NzQ= | 269 | Error in metric.compute: missing `original_instructions` argument | {
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```python
import nlp
rte_metric = nlp.load_metric('glue', name="rte")
rte_metric.compute(
[0, 0, 1, 1],
[0, 1, 0, 1],
)
```
```
181 # Read the predictio... | {
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https://api.github.com/repos/huggingface/datasets/issues/268 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/268/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/268/comments | https://api.github.com/repos/huggingface/datasets/issues/268/events | https://github.com/huggingface/datasets/pull/268 | 637,848,056 | MDExOlB1bGxSZXF1ZXN0NDMzNzU5NzQ1 | 268 | add Rotten Tomatoes Movie Review sentences sentiment dataset | {
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"@jplu @thomwolf @patrickvonplaten @lhoestq -- How do I request reviewers? Thanks."
] | 1,591,977,239,000 | 1,592,466,384,000 | 1,592,466,383,000 | CONTRIBUTOR | null | Sentence-level movie reviews v1.0 from here: http://www.cs.cornell.edu/people/pabo/movie-review-data/ | {
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"I will take a look :-) "
] | 1,591,924,177,000 | 1,592,555,059,000 | 1,592,555,059,000 | MEMBER | null | I believe it is from `wmt16`
When I run
```python
wmt = nlp.load_dataset('wmt16')
```
I get:
```python
AssertionError: The dataset wmt16 with config cs-en requires manual data.
Please follow the manual download instructions: Some of the wmt configs here, require a manual download.
Please look into wm... | {
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https://api.github.com/repos/huggingface/datasets/issues/266 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/266/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/266/comments | https://api.github.com/repos/huggingface/datasets/issues/266/events | https://github.com/huggingface/datasets/pull/266 | 637,156,392 | MDExOlB1bGxSZXF1ZXN0NDMzMTk1NDgw | 266 | Add sort, shuffle, test_train_split and select methods | {
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"Nice !\r\n\r\nAlso it looks like we can have a train_test_split method for free:\r\n```python\r\ntrain_indices, test_indices = train_test_split(range(len(dataset)))\r\ntrain = dataset.sort(indices=train_indices)\r\ntest = dataset.sort(indices=test_indices)\r\n```\r\n\r\nand a shuffling method for free:\r\n```pytho... | 1,591,892,540,000 | 1,592,497,405,000 | 1,592,497,404,000 | MEMBER | null | Add a bunch of methods to reorder/split/select rows in a dataset:
- `dataset.select(indices)`: Create a new dataset with rows selected following the list/array of indices (which can have a different size than the dataset and contain duplicated indices, the only constrain is that all the integers in the list must be sm... | {
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This is an issue because `nlp` requires the updated version to work correctly.
In this PR I added en error that is shown to the user in google colab if... | {
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https://api.github.com/repos/huggingface/datasets/issues/264 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/264/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/264/comments | https://api.github.com/repos/huggingface/datasets/issues/264/events | https://github.com/huggingface/datasets/pull/264 | 637,106,170 | MDExOlB1bGxSZXF1ZXN0NDMzMTU0ODQ4 | 264 | Fix small issues creating dataset | {
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- don't force to install apache beam for commands
- fix None cache dir when using `dl_manager.download_custom`
- added new extras in `setup.py` named `dev` that contains tests and quality dependencies
- mock dataset sizes when running tests with dummy data
- add a note abou... | {
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https://api.github.com/repos/huggingface/datasets/issues/263 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/263/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/263/comments | https://api.github.com/repos/huggingface/datasets/issues/263/events | https://github.com/huggingface/datasets/issues/263 | 637,028,015 | MDU6SXNzdWU2MzcwMjgwMTU= | 263 | [Feature request] Support for external modality for language datasets | {
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"Thanks a lot, @aleSuglia for the very detailed and introductive feature request.\r\nIt seems like we could build something pretty useful here indeed.\r\n\r\nOne of the questions here is that Arrow doesn't have built-in support for generic \"tensors\" in records but there might be ways to do that in a clean way. We... | 1,591,882,938,000 | 1,640,105,946,000 | null | CONTRIBUTOR | null | # Background
In recent years many researchers have advocated that learning meanings from text-based only datasets is just like asking a human to "learn to speak by listening to the radio" [[E. Bender and A. Koller,2020](https://openreview.net/forum?id=GKTvAcb12b), [Y. Bisk et. al, 2020](https://arxiv.org/abs/2004.10... | {
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https://api.github.com/repos/huggingface/datasets/issues/262 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/262/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/262/comments | https://api.github.com/repos/huggingface/datasets/issues/262/events | https://github.com/huggingface/datasets/pull/262 | 636,702,849 | MDExOlB1bGxSZXF1ZXN0NDMyODI3Mzcz | 262 | Add new dataset ANLI Round 1 | {
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"Hello ! Thanks for adding this one :)\r\n\r\nThis looks great, you just have to do the last steps to make the CI pass.\r\nI can see that two things are missing:\r\n1. the dummy data that is used to test that the script is working as expected\r\n2. the json file with all the infos about the dataset\r\n\r\nYou can s... | 1,591,848,897,000 | 1,591,999,383,000 | 1,591,999,383,000 | CONTRIBUTOR | null | Adding new dataset [ANLI](https://github.com/facebookresearch/anli/).
I'm not familiar with how to add new dataset. Let me know if there is any issue. I only include round 1 data here. There will be round 2, round 3 and more in the future with potentially different format. I think it will be better to separate them. | {
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https://api.github.com/repos/huggingface/datasets/issues/261 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/261/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/261/comments | https://api.github.com/repos/huggingface/datasets/issues/261/events | https://github.com/huggingface/datasets/issues/261 | 636,372,380 | MDU6SXNzdWU2MzYzNzIzODA= | 261 | Downloading dataset error with pyarrow.lib.RecordBatch | {
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"When you install `nlp` for the first time on a Colab runtime, it updates the `pyarrow` library that was already on colab. This update shows this message on colab:\r\n```\r\nWARNING: The following packages were previously imported in this runtime:\r\n [pyarrow]\r\nYou must restart the runtime in order to use newly... | 1,591,805,059,000 | 1,591,886,112,000 | 1,591,886,112,000 | NONE | null | I am trying to download `sentiment140` and I have the following error
```
/usr/local/lib/python3.6/dist-packages/nlp/load.py in load_dataset(path, name, version, data_dir, data_files, split, cache_dir, download_config, download_mode, ignore_verifications, save_infos, **config_kwargs)
518 download_mode=... | {
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https://api.github.com/repos/huggingface/datasets/issues/260 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/260/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/260/comments | https://api.github.com/repos/huggingface/datasets/issues/260/events | https://github.com/huggingface/datasets/pull/260 | 636,261,118 | MDExOlB1bGxSZXF1ZXN0NDMyNDY3NDM5 | 260 | Consistency fixes | {
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https://api.github.com/repos/huggingface/datasets/issues/259 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/259/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/259/comments | https://api.github.com/repos/huggingface/datasets/issues/259/events | https://github.com/huggingface/datasets/issues/259 | 636,239,529 | MDU6SXNzdWU2MzYyMzk1Mjk= | 259 | documentation missing how to split a dataset | {
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"this seems to work for my specific problem:\r\n\r\n`self.train_ds, self.test_ds, self.val_ds = map(_prepare_ds, ('train', 'test[:25%]+test[50%:75%]', 'test[75%:]'))`",
"Currently you can indeed split a dataset using `ds_test = nlp.load_dataset('imdb, split='test[:5000]')` (works also with percentages).\r\n\r\nHo... | 1,591,795,093,000 | 1,592,518,824,000 | 1,592,518,824,000 | NONE | null | I am trying to understand how to split a dataset ( as arrow_dataset).
I know I can do something like this to access a split which is already in the original dataset :
`ds_test = nlp.load_dataset('imdb, split='test') `
But how can I split ds_test into a test and a validation set (without reading the data into m... | {
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https://api.github.com/repos/huggingface/datasets/issues/258 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/258/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/258/comments | https://api.github.com/repos/huggingface/datasets/issues/258/events | https://github.com/huggingface/datasets/issues/258 | 635,859,525 | MDU6SXNzdWU2MzU4NTk1MjU= | 258 | Why is dataset after tokenization far more larger than the orginal one ? | {
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"Hi ! This is because `.map` added the new column `input_ids` to the dataset, and so all the other columns were kept. Therefore the dataset size increased a lot.\r\n If you want to only keep the `input_ids` column, you can stash the other ones by specifying `remove_columns=[\"title\", \"text\"]` in the arguments of... | 1,591,752,427,000 | 1,591,793,194,000 | 1,591,793,194,000 | CONTRIBUTOR | null | I tokenize wiki dataset by `map` and cache the results.
```
def tokenize_tfm(example):
example['input_ids'] = hf_fast_tokenizer.convert_tokens_to_ids(hf_fast_tokenizer.tokenize(example['text']))
return example
wiki = nlp.load_dataset('wikipedia', '20200501.en', cache_dir=cache_dir)['train']
wiki.map(token... | {
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https://api.github.com/repos/huggingface/datasets/issues/257 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/257/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/257/comments | https://api.github.com/repos/huggingface/datasets/issues/257/events | https://github.com/huggingface/datasets/issues/257 | 635,620,979 | MDU6SXNzdWU2MzU2MjA5Nzk= | 257 | Tokenizer pickling issue fix not landed in `nlp` yet? | {
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"Yes, the new release of tokenizers solves this and should be out soon.\r\nIn the meantime, you can install it with `pip install tokenizers==0.8.0-dev2`",
"If others run into this issue, a quick fix is to use python 3.6 instead of 3.7+. Serialization differences between the 3rd party `dataclasses` package for 3.6... | 1,591,722,754,000 | 1,591,825,532,000 | 1,591,723,613,000 | NONE | null | Unless I recreate an arrow_dataset from my loaded nlp dataset myself (which I think does not use the cache by default), I get the following error when applying the map function:
```
dataset = nlp.load_dataset('cos_e')
tokenizer = GPT2TokenizerFast.from_pretrained('gpt2', cache_dir=cache_dir)
for split in datase... | {
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https://api.github.com/repos/huggingface/datasets/issues/256 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/256/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/256/comments | https://api.github.com/repos/huggingface/datasets/issues/256/events | https://github.com/huggingface/datasets/issues/256 | 635,596,295 | MDU6SXNzdWU2MzU1OTYyOTU= | 256 | [Feature request] Add a feature to dataset | {
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"Do you have an example of what you would like to do? (you can just add a field in the output of the unction you give to map and this will add this field in the output table)",
"Given another source of data loaded in, I want to pre-add it to the dataset so that it aligns with the indices of the arrow dataset prio... | 1,591,720,692,000 | 1,591,721,502,000 | 1,591,721,502,000 | NONE | null | Is there a straightforward way to add a field to the arrow_dataset, prior to performing map? | {
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https://api.github.com/repos/huggingface/datasets/issues/255 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/255/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/255/comments | https://api.github.com/repos/huggingface/datasets/issues/255/events | https://github.com/huggingface/datasets/pull/255 | 635,300,822 | MDExOlB1bGxSZXF1ZXN0NDMxNjg3MDM0 | 255 | Add dataset/piaf | {
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"Very nice !"
] | 1,591,697,761,000 | 1,591,950,687,000 | 1,591,950,687,000 | CONTRIBUTOR | null | Small SQuAD-like French QA dataset [PIAF](https://www.aclweb.org/anthology/2020.lrec-1.673.pdf) | {
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https://api.github.com/repos/huggingface/datasets/issues/254 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/254/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/254/comments | https://api.github.com/repos/huggingface/datasets/issues/254/events | https://github.com/huggingface/datasets/issues/254 | 635,057,568 | MDU6SXNzdWU2MzUwNTc1Njg= | 254 | [Feature request] Be able to remove a specific sample of the dataset | {
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"Oh yes you can now do that with the `dataset.filter()` method that was added in #214 "
] | 1,591,669,333,000 | 1,591,692,098,000 | 1,591,692,098,000 | NONE | null | As mentioned in #117, it's currently not possible to remove a sample of the dataset.
But it is a important use case : After applying some preprocessing, some samples might be empty for example. We should be able to remove these samples from the dataset, or at least mark them as `removed` so when iterating the datase... | {
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"The dummy data file was wrong. I only fixed it for the book config. Even though the tests are all green here, this should also be fixed for all other configs. Could you take a look there @mariamabarham ? ",
"Hi @mariamabarham \r\n\r\nFLUE can indeed become a very interesting benchmark for french NLP !\r\nUnfortu... | 1,591,636,269,000 | 1,594,885,859,000 | 1,594,885,859,000 | CONTRIBUTOR | null | This PR add the Flue dataset as requested in this issue #223 . @lbourdois made a detailed description in that issue.
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