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https://api.github.com/repos/huggingface/datasets/issues/478 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/478/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/478/comments | https://api.github.com/repos/huggingface/datasets/issues/478/events | https://github.com/huggingface/datasets/issues/478 | 673,178,317 | MDU6SXNzdWU2NzMxNzgzMTc= | 478 | Export TFRecord to GCP bucket | {
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"Nevermind, I restarted my python session and it worked fine...\r\n\r\n---\r\n\r\nI had an authentification error, and I authenticated from another terminal. After that, no more error but it was not working. Restarting the sessions makes it work :)"
] | 2020-08-05T01:08:32 | 2020-08-05T01:21:37 | 2020-08-05T01:21:36 | NONE | null | null | null | null | Previously, I was writing TFRecords manually to GCP bucket with : `with tf.io.TFRecordWriter('gs://my_bucket/x.tfrecord')`
Since `0.4.0` is out with the `export()` function, I tried it. But it seems TFRecords cannot be directly written to GCP bucket.
`dataset.export('local.tfrecord')` works fine,
but `dataset.... | {
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https://api.github.com/repos/huggingface/datasets/issues/477 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/477/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/477/comments | https://api.github.com/repos/huggingface/datasets/issues/477/events | https://github.com/huggingface/datasets/issues/477 | 673,142,143 | MDU6SXNzdWU2NzMxNDIxNDM= | 477 | Overview.ipynb throws exceptions with nlp 0.4.0 | {
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"Thanks for reporting this issue\r\n\r\nThere was a bug where numpy arrays would get returned instead of tensorflow tensors.\r\nThis is fixed on master.\r\n\r\nI tried to re-run the colab and encountered this error instead:\r\n\r\n```\r\nAttributeError: 'tensorflow.python.framework.ops.EagerTensor' object has no at... | 2020-08-04T23:18:15 | 2021-08-03T06:02:15 | 2021-08-03T06:02:15 | NONE | null | null | null | null | with nlp 0.4.0, the TensorFlow example in Overview.ipynb throws the following exceptions:
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-5-48907f2ad433> in <module>
----> 1 features = {x: trai... | {
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https://api.github.com/repos/huggingface/datasets/issues/474 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/474/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/474/comments | https://api.github.com/repos/huggingface/datasets/issues/474/events | https://github.com/huggingface/datasets/issues/474 | 672,407,330 | MDU6SXNzdWU2NzI0MDczMzA= | 474 | test_load_real_dataset when config has BUILDER_CONFIGS that matter | {
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"The `data_dir` parameter has been removed. Now the error is `ValueError: Config name is missing`\r\n\r\nAs mentioned in #470 I think we can have one test with the first config of BUILDER_CONFIGS, and another test that runs all of the configs in BUILDER_CONFIGS",
"This was fixed in #527 \r\n\r\nClosing this one, ... | 2020-08-03T23:46:36 | 2020-09-07T14:53:13 | 2020-09-07T14:53:13 | NONE | null | null | null | null | It a dataset has custom `BUILDER_CONFIGS` with non-keyword arguments (or keyword arguments with non default values), the config is not loaded during the test and causes an error.
I think the problem is that `test_load_real_dataset` calls `load_dataset` with `data_dir=temp_data_dir` ([here](https://github.com/huggingfa... | {
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https://api.github.com/repos/huggingface/datasets/issues/469 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/469/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/469/comments | https://api.github.com/repos/huggingface/datasets/issues/469/events | https://github.com/huggingface/datasets/issues/469 | 671,876,963 | MDU6SXNzdWU2NzE4NzY5NjM= | 469 | invalid data type 'str' at _convert_outputs in arrow_dataset.py | {
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"Hi ! Did you try to set the output format to pytorch ? (or tensorflow if you're using tensorflow)\r\nIt can be done with `dataset.set_format(\"torch\", columns=columns)` (or \"tensorflow\").\r\n\r\nNote that for pytorch, string columns can't be converted to `torch.Tensor`, so you have to specify in `columns=` the... | 2020-08-03T07:48:29 | 2023-07-20T15:54:17 | 2023-07-20T15:54:17 | NONE | null | null | null | null | I trying to build multi label text classifier model using Transformers lib.
I'm using Transformers NLP to load the data set, while calling trainer.train() method. It throws the following error
File "C:\***\arrow_dataset.py", line 343, in _convert_outputs
v = command(v)
TypeError: new(): invalid data type ... | {
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https://api.github.com/repos/huggingface/datasets/issues/468 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/468/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/468/comments | https://api.github.com/repos/huggingface/datasets/issues/468/events | https://github.com/huggingface/datasets/issues/468 | 671,622,441 | MDU6SXNzdWU2NzE2MjI0NDE= | 468 | UnicodeDecodeError while loading PAN-X task of XTREME dataset | {
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"Indeed. Solution 1 is the simplest.\r\n\r\nThis is actually a recurring problem.\r\nI think we should scan all the datasets with regexpr to fix the use of `open()` without encodings.\r\nAnd probably add a test in the CI to forbid using this in the future.",
"I'm happy to tackle the broader problem - will open a ... | 2020-08-02T14:05:10 | 2020-08-20T08:16:08 | 2020-08-20T08:16:08 | MEMBER | null | null | null | null | Hi 🤗 team!
## Description of the problem
I'm running into a `UnicodeDecodeError` while trying to load the PAN-X subset the XTREME dataset:
```
---------------------------------------------------------------------------
UnicodeDecodeError Traceback (most recent call last)
<ipython-inp... | {
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https://api.github.com/repos/huggingface/datasets/issues/445 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/445/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/445/comments | https://api.github.com/repos/huggingface/datasets/issues/445/events | https://github.com/huggingface/datasets/issues/445 | 666,836,658 | MDU6SXNzdWU2NjY4MzY2NTg= | 445 | DEFAULT_TOKENIZER import error in sacrebleu | {
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"This issue was resolved by #447 "
] | 2020-07-28T07:31:30 | 2020-07-28T12:58:56 | 2020-07-28T12:58:56 | CONTRIBUTOR | null | null | null | null | Latest Version 0.3.0
When loading the metric "sacrebleu" there is an import error due to the wrong path
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"Same here !",
"This is the only fix I could come up with without touching the repo's code.\r\n```python\r\nfrom nlp.builder import FORCE_REDOWNLOAD\r\ndataset = load_dataset('csv', data_file='./a.csv', download_mode=FORCE_REDOWNLOAD, version='0.0.1')\r\n```\r\nYou'll have to change the version each time you want... | 2020-07-27T13:08:06 | 2020-07-29T13:57:22 | 2020-07-29T13:57:22 | NONE | null | null | null | null | I used load a file called 'a.csv' by
```
dataset = load_dataset('csv', data_file='./a.csv')
```
And after a while, I tried to load another csv called 'b.csv'
```
dataset = load_dataset('csv', data_file='./b.csv')
```
However, the new dataset seems to remain the old 'a.csv' and not loading new csv file.
Even... | {
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https://api.github.com/repos/huggingface/datasets/issues/443 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/443/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/443/comments | https://api.github.com/repos/huggingface/datasets/issues/443/events | https://github.com/huggingface/datasets/issues/443 | 666,246,716 | MDU6SXNzdWU2NjYyNDY3MTY= | 443 | Cannot unpickle saved .pt dataset with torch.save()/load() | {
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"This seems to be fixed in a non-released version. \r\n\r\nInstalling nlp from source\r\n```\r\ngit clone https://github.com/huggingface/nlp\r\ncd nlp\r\npip install .\r\n```\r\nsolves the issue. "
] | 2020-07-27T12:13:37 | 2020-07-27T13:05:11 | 2020-07-27T13:05:11 | CONTRIBUTOR | null | null | null | null | Saving a formatted torch dataset to file using `torch.save()`. Loading the same file fails during unpickling:
```python
>>> import torch
>>> import nlp
>>> squad = nlp.load_dataset("squad.py", split="train")
>>> squad
Dataset(features: {'source_text': Value(dtype='string', id=None), 'target_text': Value(dtype... | {
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] | open | false | null | [] | [] | 2020-07-27T10:59:58 | 2020-08-24T15:13:20 | null | NONE | null | null | null | null | Hello! First of all, thanks for setting up this useful project!
I've just realised you provide the the [Glue Diagnostics Data](https://huggingface.co/nlp/viewer/?dataset=glue&config=ax) without labels, indicating in the `GlueConfig` that you've only a test set.
Yet, the data with labels is available, too (see als... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/439 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/439/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/439/comments | https://api.github.com/repos/huggingface/datasets/issues/439/events | https://github.com/huggingface/datasets/issues/439 | 665,964,673 | MDU6SXNzdWU2NjU5NjQ2NzM= | 439 | Issues: Adding a FAISS or Elastic Search index to a Dataset | {
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"`DPRContextEncoder` and `DPRContextEncoderTokenizer` will be available in the next release of `transformers`.\r\n\r\nRight now you can experiment with it by installing `transformers` from the master branch.\r\nYou can also check the docs of DPR [here](https://huggingface.co/transformers/master/model_doc/dpr.html).... | 2020-07-27T04:25:17 | 2020-10-28T01:46:24 | 2020-10-28T01:46:24 | NONE | null | null | null | null | It seems the DPRContextEncoder, DPRContextEncoderTokenizer cited[ in this documentation](https://huggingface.co/nlp/faiss_and_ea.html) is not implemented ? It didnot work with the standard nlp installation . Also, I couldn't find or use it with the latest nlp install from github in Colab. Is there any dependency on t... | {
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https://api.github.com/repos/huggingface/datasets/issues/438 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/438/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/438/comments | https://api.github.com/repos/huggingface/datasets/issues/438/events | https://github.com/huggingface/datasets/issues/438 | 665,865,490 | MDU6SXNzdWU2NjU4NjU0OTA= | 438 | New Datasets: IWSLT15+, ITTB | {
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"Thanks Sam, we now have a very detailed tutorial and template on how to add a new dataset to the library. It typically take 1-2 hours to add one. Do you want to give it a try ?\r\nThe tutorial on writing a new dataset loading script is here: https://huggingface.co/nlp/add_dataset.html\r\nAnd the part on how to sha... | 2020-07-26T21:43:04 | 2020-08-24T15:12:15 | null | CONTRIBUTOR | null | null | null | null | **Links:**
[iwslt](https://pytorchnlp.readthedocs.io/en/latest/_modules/torchnlp/datasets/iwslt.html)
Don't know if that link is up to date.
[ittb](http://www.cfilt.iitb.ac.in/iitb_parallel/)
**Motivation**: replicate mbart finetuning results (table below)
![image](https://user-images.githubusercontent.com/60450... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/436 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/436/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/436/comments | https://api.github.com/repos/huggingface/datasets/issues/436/events | https://github.com/huggingface/datasets/issues/436 | 665,582,167 | MDU6SXNzdWU2NjU1ODIxNjc= | 436 | Google Colab - load_dataset - PyArrow exception | {
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"Indeed, we’ll make a new PyPi release next week to solve this. Cc @lhoestq ",
"+1! this is the reason our tests are failing at [TextAttack](https://github.com/QData/TextAttack) \r\n\r\n(Though it's worth noting if we fixed the version number of pyarrow to 0.16.0 that would fix our problem too. But in this case w... | 2020-07-25T13:05:20 | 2020-08-20T08:08:18 | 2020-08-20T08:08:18 | NONE | null | null | null | null | With latest PyArrow 1.0.0 installed, I get the following exception . Restarting colab has the same issue
ImportWarning: To use `nlp`, the module `pyarrow>=0.16.0` is required, and the current version of `pyarrow` doesn't match this condition. If you are running this in a Google Colab, you should probably just rest... | {
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https://api.github.com/repos/huggingface/datasets/issues/435 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/435/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/435/comments | https://api.github.com/repos/huggingface/datasets/issues/435/events | https://github.com/huggingface/datasets/issues/435 | 665,507,141 | MDU6SXNzdWU2NjU1MDcxNDE= | 435 | ImportWarning for pyarrow 1.0.0 | {
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"This was fixed in #434 \r\nWe'll do a release later this week to include this fix.\r\nThanks for reporting",
"I dont know if the fix was made but the problem is still present : \r\nInstaled with pip : NLP 0.3.0 // pyarrow 1.0.0 \r\nOS : archlinux with kernel zen 5.8.5",
"Yes it was fixed in `nlp>=0.4.0`\r\nYou... | 2020-07-25T03:44:39 | 2020-09-08T17:57:15 | 2020-08-03T16:37:32 | NONE | null | null | null | null | The following PR raised ImportWarning at `pyarrow ==1.0.0` https://github.com/huggingface/nlp/pull/265/files | {
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https://api.github.com/repos/huggingface/datasets/issues/433 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/433/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/433/comments | https://api.github.com/repos/huggingface/datasets/issues/433/events | https://github.com/huggingface/datasets/issues/433 | 665,311,025 | MDU6SXNzdWU2NjUzMTEwMjU= | 433 | How to reuse functionality of a (generic) dataset? | {
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"Hi @ArneBinder, we have a few \"generic\" datasets which are intended to load data files with a predefined format:\r\n- csv: https://github.com/huggingface/nlp/tree/master/datasets/csv\r\n- json: https://github.com/huggingface/nlp/tree/master/datasets/json\r\n- text: https://github.com/huggingface/nlp/tree/master/... | 2020-07-24T17:27:37 | 2022-10-04T17:59:34 | 2022-10-04T17:59:33 | NONE | null | null | null | null | I have written a generic dataset for corpora created with the Brat annotation tool ([specification](https://brat.nlplab.org/standoff.html), [dataset code](https://github.com/ArneBinder/nlp/blob/brat/datasets/brat/brat.py)). Now I wonder how to use that to create specific dataset instances. What's the recommended way to... | {
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https://api.github.com/repos/huggingface/datasets/issues/426 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/426/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/426/comments | https://api.github.com/repos/huggingface/datasets/issues/426/events | https://github.com/huggingface/datasets/issues/426 | 664,203,897 | MDU6SXNzdWU2NjQyMDM4OTc= | 426 | [FEATURE REQUEST] Multiprocessing with for dataset.map, dataset.filter | {
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"Yes that's definitely something we plan to add ^^",
"Yes, that would be nice. We could take a look at what tensorflow `tf.data` does under the hood for instance.",
"So `tf.data.Dataset.map()` returns a `ParallelMapDataset` if `num_parallel_calls is not None` [link](https://github.com/tensorflow/tensorflow/blob... | 2020-07-23T05:00:41 | 2021-03-12T09:34:12 | 2020-09-07T14:48:04 | NONE | null | null | null | null | It would be nice to be able to speed up `dataset.map` or `dataset.filter`. Perhaps this is as easy as sharding the dataset sending each shard to a process/thread/dask pool and using the new `nlp.concatenate_dataset()` function to join them all together? | {
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https://api.github.com/repos/huggingface/datasets/issues/425 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/425/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/425/comments | https://api.github.com/repos/huggingface/datasets/issues/425/events | https://github.com/huggingface/datasets/issues/425 | 664,029,848 | MDU6SXNzdWU2NjQwMjk4NDg= | 425 | Correct data structure for PAN-X task in XTREME dataset? | {
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"Thanks for noticing ! This looks more reasonable indeed.\r\nFeel free to open a PR",
"Hi @lhoestq \r\nI made the proposed changes to the `xtreme.py` script. I noticed that I also need to change the schema in the `dataset_infos.json` file. More specifically the `\"features\"` part of the PAN-X.LANG dataset:\r\n\... | 2020-07-22T20:29:20 | 2020-08-02T13:30:34 | 2020-08-02T13:30:34 | MEMBER | null | null | null | null | Hi 🤗 team!
## Description of the problem
Thanks to the fix from #416 I am now able to load the NER task in the XTREME dataset as follows:
```python
from nlp import load_dataset
# AmazonPhotos.zip is located in data/
dataset = load_dataset("xtreme", "PAN-X.en", data_dir='./data')
dataset_train = dataset['tr... | {
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https://api.github.com/repos/huggingface/datasets/issues/418 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/418/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/418/comments | https://api.github.com/repos/huggingface/datasets/issues/418/events | https://github.com/huggingface/datasets/issues/418 | 661,914,873 | MDU6SXNzdWU2NjE5MTQ4NzM= | 418 | Addition of google drive links to dl_manager | {
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"I think the problem is the way you wrote your urls. Try the following structure to see `https://drive.google.com/uc?export=download&id=your_file_id` . \r\n\r\n@lhoestq ",
"Oh sorry, I think `_get_drive_url` is doing that. \r\n\r\nHave you tried to use `dl_manager.download_and_extract(_get_drive_url(_TRAIN_URL)`... | 2020-07-20T14:52:02 | 2020-07-20T15:39:32 | 2020-07-20T15:39:32 | CONTRIBUTOR | null | null | null | null | Hello there, I followed the template to create a download script of my own, which works fine for me, although I had to shun the dl_manager because it was downloading nothing from the drive links and instead use gdown.
This is the script for me:
```python
class EmoConfig(nlp.BuilderConfig):
"""BuilderConfig ... | {
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https://api.github.com/repos/huggingface/datasets/issues/415 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/415/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/415/comments | https://api.github.com/repos/huggingface/datasets/issues/415/events | https://github.com/huggingface/datasets/issues/415 | 660,687,076 | MDU6SXNzdWU2NjA2ODcwNzY= | 415 | Something is wrong with WMT 19 kk-en dataset | {
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] | open | false | null | [] | [] | 2020-07-19T08:18:51 | 2020-07-20T09:54:26 | null | NONE | null | null | null | null | The translation in the `train` set does not look right:
```
>>>import nlp
>>>from nlp import load_dataset
>>>dataset = load_dataset('wmt19', 'kk-en')
>>>dataset["train"]["translation"][0]
{'kk': 'Trumpian Uncertainty', 'en': 'Трамптық белгісіздік'}
>>>dataset["validation"]["translation"][0]
{'kk': 'Ақша-несие... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/414 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/414/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/414/comments | https://api.github.com/repos/huggingface/datasets/issues/414/events | https://github.com/huggingface/datasets/issues/414 | 660,654,013 | MDU6SXNzdWU2NjA2NTQwMTM= | 414 | from_dict delete? | {
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"`from_dict` was added in #350 that was unfortunately not included in the 0.3.0 release. It's going to be included in the next release that will be out pretty soon though.\r\nRight now if you want to use `from_dict` you have to install the package from the master branch\r\n```\r\npip install git+https://github.com/... | 2020-07-19T07:08:36 | 2020-07-21T02:21:17 | 2020-07-21T02:21:17 | NONE | null | null | null | null | AttributeError: type object 'Dataset' has no attribute 'from_dict' | {
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https://api.github.com/repos/huggingface/datasets/issues/413 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/413/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/413/comments | https://api.github.com/repos/huggingface/datasets/issues/413/events | https://github.com/huggingface/datasets/issues/413 | 660,063,655 | MDU6SXNzdWU2NjAwNjM2NTU= | 413 | Is there a way to download only NQ dev? | {
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"Unfortunately it's not possible to download only the dev set of NQ.\r\n\r\nI think we could add a way to download only the test set by adding a custom configuration to the processing script though.",
"Ok, got it. I think this could be a valuable feature - especially for large datasets like NQ, but potentially al... | 2020-07-18T10:28:23 | 2022-02-11T09:50:21 | 2022-02-11T09:50:21 | NONE | null | null | null | null | Maybe I missed that in the docs, but is there a way to only download the dev set of natural questions (~1 GB)?
As we want to benchmark QA models on different datasets, I would like to avoid downloading the 41GB of training data.
I tried
```
dataset = nlp.load_dataset('natural_questions', split="validation", bea... | {
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https://api.github.com/repos/huggingface/datasets/issues/412 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/412/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/412/comments | https://api.github.com/repos/huggingface/datasets/issues/412/events | https://github.com/huggingface/datasets/issues/412 | 660,047,139 | MDU6SXNzdWU2NjAwNDcxMzk= | 412 | Unable to load XTREME dataset from disk | {
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"Hi @lewtun, you have to provide the full path to the downloaded file for example `/home/lewtum/..`",
"I was able to repro. Opening a PR to fix that.\r\nThanks for reporting this issue !",
"Thanks for the rapid fix @lhoestq!"
] | 2020-07-18T09:55:00 | 2020-07-21T08:15:44 | 2020-07-21T08:15:44 | MEMBER | null | null | null | null | Hi 🤗 team!
## Description of the problem
Following the [docs](https://huggingface.co/nlp/loading_datasets.html?highlight=xtreme#manually-downloading-files) I'm trying to load the `PAN-X.fr` dataset from the [XTREME](https://github.com/google-research/xtreme) benchmark.
I have manually downloaded the `AmazonPho... | {
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https://api.github.com/repos/huggingface/datasets/issues/409 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/409/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/409/comments | https://api.github.com/repos/huggingface/datasets/issues/409/events | https://github.com/huggingface/datasets/issues/409 | 659,128,611 | MDU6SXNzdWU2NTkxMjg2MTE= | 409 | train_test_split error: 'dict' object has no attribute 'deepcopy' | {
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"It was fixed in 2ddd18d139d3047c9c3abe96e1e7d05bb360132c.\r\nCould you pull the latest changes from master @morganmcg1 ?",
"Thanks @lhoestq, works fine now!"
] | 2020-07-17T10:36:28 | 2020-07-21T14:34:52 | 2020-07-21T14:34:52 | NONE | null | null | null | null | `train_test_split` is giving me an error when I try and call it:
`'dict' object has no attribute 'deepcopy'`
## To reproduce
```
dataset = load_dataset('glue', 'mrpc', split='train')
dataset = dataset.train_test_split(test_size=0.2)
```
## Full Stacktrace
```
-------------------------------------------... | {
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https://api.github.com/repos/huggingface/datasets/issues/407 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/407/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/407/comments | https://api.github.com/repos/huggingface/datasets/issues/407/events | https://github.com/huggingface/datasets/issues/407 | 658,672,736 | MDU6SXNzdWU2NTg2NzI3MzY= | 407 | MissingBeamOptions for Wikipedia 20200501.en | {
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"Fixed. Could you try again @mitchellgordon95 ?\r\nIt was due a file not being updated on S3.\r\n\r\nWe need to make sure all the datasets scripts get updated properly @julien-c ",
"Works for me! Thanks.",
"I found the same issue with almost any language other than English. (For English, it works). Will someone... | 2020-07-16T23:48:03 | 2021-01-12T11:41:16 | 2020-07-17T14:24:28 | CONTRIBUTOR | null | null | null | null | There may or may not be a regression for the pre-processed Wikipedia dataset. This was working fine 10 commits ago (without having Apache Beam available):
```
nlp.load_dataset('wikipedia', "20200501.en", split='train')
```
And now, having pulled master, I get:
```
Downloading and preparing dataset wikipedia... | {
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https://api.github.com/repos/huggingface/datasets/issues/406 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/406/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/406/comments | https://api.github.com/repos/huggingface/datasets/issues/406/events | https://github.com/huggingface/datasets/issues/406 | 658,581,764 | MDU6SXNzdWU2NTg1ODE3NjQ= | 406 | Faster Shuffling? | {
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"I think the slowness here probably come from the fact that we are copying from and to python.\r\n\r\n@lhoestq for all the `select`-based methods I think we should stay in Arrow format and update the writer so that it can accept Arrow tables or batches as well. What do you think?",
"> @lhoestq for all the `select... | 2020-07-16T21:21:53 | 2023-08-16T09:52:39 | 2020-09-07T14:45:25 | CONTRIBUTOR | null | null | null | null | Consider shuffling bookcorpus:
```
dataset = nlp.load_dataset('bookcorpus', split='train')
dataset.shuffle()
```
According to tqdm, this will take around 2.5 hours on my machine to complete (even with the faster version of select from #405). I've also tried with `keep_in_memory=True` and `writer_batch_size=1000`... | {
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https://api.github.com/repos/huggingface/datasets/issues/395 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/395/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/395/comments | https://api.github.com/repos/huggingface/datasets/issues/395/events | https://github.com/huggingface/datasets/issues/395 | 657,454,983 | MDU6SXNzdWU2NTc0NTQ5ODM= | 395 | Memory issue when doing select | {
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```python
import nlp
w = nlp.load_dataset("wikipedia", "20200501.en", split="train")
w.select([0])
```
This is caused by [this line](https://github.com/huggingface/nlp/blob/master/src/nlp/arrow_dataset.py#L626) for some reason, that ... | {
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"similar slow download speed here for nlp.load_dataset('wmt14', 'fr-en')\r\n`\r\nDownloading: 100%|██████████████████████████████████████████████████████████| 658M/658M [1:00:42<00:00, 181kB/s]\r\nDownloading: 100%|██████████████████████████████████████████████████████████| 918M/918M [1:39:38<00:00, 154kB/s]\r\nDow... | 2020-07-14T15:36:41 | 2022-10-04T18:01:28 | 2022-10-04T18:01:28 | NONE | null | null | null | null | 1. I try downloading `wmt14`, `wmt15`, `wmt17`, `wmt19` with the following code:
```
nlp.load_dataset('wmt14','de-en')
nlp.load_dataset('wmt15','de-en')
nlp.load_dataset('wmt17','de-en')
nlp.load_dataset('wmt19','de-en')
```
The code runs but the download speed is **extremely slow**, the same behaviour is not ob... | {
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https://api.github.com/repos/huggingface/datasets/issues/387 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/387/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/387/comments | https://api.github.com/repos/huggingface/datasets/issues/387/events | https://github.com/huggingface/datasets/issues/387 | 656,361,357 | MDU6SXNzdWU2NTYzNjEzNTc= | 387 | Conversion through to_pandas output numpy arrays for lists instead of python objects | {
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"To convert from arrow type we have three options: to_numpy, to_pandas and to_pydict/to_pylist.\r\n\r\n- to_numpy and to_pandas return numpy arrays instead of lists but are very fast.\r\n- to_pydict/to_pylist can be 100x slower and become the bottleneck for reading data, but at least they return lists.\r\n\r\nMaybe... | 2020-07-14T06:24:01 | 2020-07-17T11:37:00 | 2020-07-17T11:37:00 | MEMBER | null | null | null | null | In a related question, the conversion through to_pandas output numpy arrays for the lists instead of python objects.
Here is an example:
```python
>>> dataset._data.slice(key, 1).to_pandas().to_dict("list")
{'sentence1': ['Amrozi accused his brother , whom he called " the witness " , of deliberately distorting hi... | {
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https://api.github.com/repos/huggingface/datasets/issues/382 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/382/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/382/comments | https://api.github.com/repos/huggingface/datasets/issues/382/events | https://github.com/huggingface/datasets/issues/382 | 655,290,482 | MDU6SXNzdWU2NTUyOTA0ODI= | 382 | 1080 | {
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https://api.github.com/repos/huggingface/datasets/issues/381 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/381/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/381/comments | https://api.github.com/repos/huggingface/datasets/issues/381/events | https://github.com/huggingface/datasets/issues/381 | 655,277,119 | MDU6SXNzdWU2NTUyNzcxMTk= | 381 | NLp | {
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https://api.github.com/repos/huggingface/datasets/issues/378 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/378/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/378/comments | https://api.github.com/repos/huggingface/datasets/issues/378/events | https://github.com/huggingface/datasets/issues/378 | 655,226,316 | MDU6SXNzdWU2NTUyMjYzMTY= | 378 | [dataset] Structure of MLQA seems unecessary nested | {
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"Same for the RACE dataset: https://github.com/huggingface/nlp/blob/master/datasets/race/race.py\r\n\r\nShould we scan all the datasets to remove this pattern of un-necessary nesting?",
"You're right, I think we don't need to use the nested dictionary. \r\n"
] | 2020-07-11T15:16:08 | 2020-07-15T16:17:20 | 2020-07-15T16:17:20 | MEMBER | null | null | null | null | The features of the MLQA dataset comprise several nested dictionaries with a single element inside (for `questions` and `ids`): https://github.com/huggingface/nlp/blob/master/datasets/mlqa/mlqa.py#L90-L97
Should we keep this @mariamabarham @patrickvonplaten? Was this added for compatibility with tfds?
```python
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https://api.github.com/repos/huggingface/datasets/issues/377 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/377/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/377/comments | https://api.github.com/repos/huggingface/datasets/issues/377/events | https://github.com/huggingface/datasets/issues/377 | 655,215,790 | MDU6SXNzdWU2NTUyMTU3OTA= | 377 | Iyy!!! | {
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https://api.github.com/repos/huggingface/datasets/issues/376 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/376/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/376/comments | https://api.github.com/repos/huggingface/datasets/issues/376/events | https://github.com/huggingface/datasets/issues/376 | 655,047,826 | MDU6SXNzdWU2NTUwNDc4MjY= | 376 | to_pandas conversion doesn't always work | {
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"**Edit**: other topic previously in this message moved to a new issue: https://github.com/huggingface/nlp/issues/387",
"Could you try to update pyarrow to >=0.17.0 ? It should fix the `to_pandas` bug\r\n\r\nAlso I'm not sure that structures like list<struct> are fully supported in the lib (none of the datasets u... | 2020-07-10T21:33:31 | 2022-10-04T18:05:39 | 2022-10-04T18:05:39 | MEMBER | null | null | null | null | For some complex nested types, the conversion from Arrow to python dict through pandas doesn't seem to be possible.
Here is an example using the official SQUAD v2 JSON file.
This example was found while investigating #373.
```python
>>> squad = load_dataset('json', data_files={nlp.Split.TRAIN: ["./train-v2.0.... | {
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https://api.github.com/repos/huggingface/datasets/issues/375 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/375/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/375/comments | https://api.github.com/repos/huggingface/datasets/issues/375/events | https://github.com/huggingface/datasets/issues/375 | 655,023,307 | MDU6SXNzdWU2NTUwMjMzMDc= | 375 | TypeError when computing bertscore | {
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"I am not able to reproduce this issue on my side.\r\nCould you give us more details about the inputs you used ?\r\n\r\nI do get another error though:\r\n```\r\n~/.virtualenvs/hf-datasets/lib/python3.7/site-packages/bert_score/utils.py in bert_cos_score_idf(model, refs, hyps, tokenizer, idf_dict, verbose, batch_siz... | 2020-07-10T20:37:44 | 2022-06-01T15:15:59 | 2022-06-01T15:15:59 | NONE | null | null | null | null | Hi,
I installed nlp 0.3.0 via pip, and my python version is 3.7.
When I tried to compute bertscore with the code:
```
import nlp
bertscore = nlp.load_metric('bertscore')
# load hyps and refs
...
print (bertscore.compute(hyps, refs, lang='en'))
```
I got the following error.
```
Traceback (most rece... | {
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https://api.github.com/repos/huggingface/datasets/issues/373 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/373/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/373/comments | https://api.github.com/repos/huggingface/datasets/issues/373/events | https://github.com/huggingface/datasets/issues/373 | 654,845,133 | MDU6SXNzdWU2NTQ4NDUxMzM= | 373 | Segmentation fault when loading local JSON dataset as of #372 | {
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"I've seen this sort of thing before -- it might help to delete the directory -- I've also noticed that there is an error with the json Dataloader for any data I've tried to load. I've replaced it with this, which skips over the data feature population step:\r\n\r\n\r\n```python\r\nimport os\r\n\r\nimport pyarrow.j... | 2020-07-10T15:04:25 | 2022-10-04T18:05:47 | 2022-10-04T18:05:47 | CONTRIBUTOR | null | null | null | null | The last issue was closed (#369) once the #372 update was merged. However, I'm still not able to load a SQuAD formatted JSON file. Instead of the previously recorded pyarrow error, I now get a segmentation fault.
```
dataset = nlp.load_dataset('json', data_files={nlp.Split.TRAIN: ["./datasets/train-v2.0.json"]}, f... | {
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https://api.github.com/repos/huggingface/datasets/issues/369 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/369/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/369/comments | https://api.github.com/repos/huggingface/datasets/issues/369/events | https://github.com/huggingface/datasets/issues/369 | 654,186,890 | MDU6SXNzdWU2NTQxODY4OTA= | 369 | can't load local dataset: pyarrow.lib.ArrowInvalid: straddling object straddles two block boundaries | {
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"I am able to reproduce this with the official SQuAD `train-v2.0.json` file downloaded directly from https://rajpurkar.github.io/SQuAD-explorer/",
"I am facing this issue in transformers library 3.0.2 while reading a csv using datasets.\r\nIs this fixed in latest version? \r\nI updated the latest version 4.0.1 bu... | 2020-07-09T16:16:53 | 2020-12-15T23:07:22 | 2020-07-10T14:52:06 | CONTRIBUTOR | null | null | null | null | Trying to load a local SQuAD-formatted dataset (from a JSON file, about 60MB):
```
dataset = nlp.load_dataset(path='json', data_files={nlp.Split.TRAIN: ["./path/to/file.json"]})
```
causes
```
Traceback (most recent call last):
File "dataloader.py", line 9, in <module>
["./path/to/file.json"]})
File "/... | {
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https://api.github.com/repos/huggingface/datasets/issues/368 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/368/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/368/comments | https://api.github.com/repos/huggingface/datasets/issues/368/events | https://github.com/huggingface/datasets/issues/368 | 654,087,251 | MDU6SXNzdWU2NTQwODcyNTE= | 368 | load_metric can't acquire lock anymore | {
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"I found that, in the same process (or the same interactive session), if I do\r\n\r\nimport nlp\r\n\r\nm1 = nlp.load_metric('glue', 'mrpc')\r\nm2 = nlp.load_metric('glue', 'sst2')\r\n\r\nI will get the same error `ValueError: Cannot acquire lock, caching file might be used by another process, you should setup a uni... | 2020-07-09T14:04:09 | 2020-07-10T13:45:20 | 2020-07-10T13:45:20 | NONE | null | null | null | null | I can't load metric (glue) anymore after an error in a previous run. I even removed the whole cache folder `/home/XXX/.cache/huggingface/`, and the issue persisted. What are the steps to fix this?
Traceback (most recent call last):
File "/home/XXX/miniconda3/envs/ML-DL-py-3.7/lib/python3.7/site-packages/n... | {
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https://api.github.com/repos/huggingface/datasets/issues/365 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/365/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/365/comments | https://api.github.com/repos/huggingface/datasets/issues/365/events | https://github.com/huggingface/datasets/issues/365 | 653,845,964 | MDU6SXNzdWU2NTM4NDU5NjQ= | 365 | How to augment data ? | {
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"Using batched map is probably the easiest way at the moment.\r\nWhat kind of augmentation would you like to do ?",
"Some samples in the dataset are too long, I want to divide them in several samples.",
"Using batched map is the way to go then.\r\nWe'll make it clearer in the docs that map could be used for aug... | 2020-07-09T07:52:37 | 2020-07-10T09:12:07 | 2020-07-10T08:22:15 | NONE | null | null | null | null | Is there any clean way to augment data ?
For now my work-around is to use batched map, like this :
```python
def aug(samples):
# Simply copy the existing data to have x2 amount of data
for k, v in samples.items():
samples[k].extend(v)
return samples
dataset = dataset.map(aug, batched=T... | {
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https://api.github.com/repos/huggingface/datasets/issues/362 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/362/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/362/comments | https://api.github.com/repos/huggingface/datasets/issues/362/events | https://github.com/huggingface/datasets/issues/362 | 653,766,245 | MDU6SXNzdWU2NTM3NjYyNDU= | 362 | [dateset subset missing] xtreme paws-x | {
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"You're right, thanks for pointing it out. We will update it "
] | 2020-07-09T05:04:54 | 2020-07-09T12:38:42 | 2020-07-09T12:38:42 | CONTRIBUTOR | null | null | null | null | I tried nlp.load_dataset('xtreme', 'PAWS-X.es') but get the value error
It turns out that the subset for Spanish is missing
https://github.com/google-research-datasets/paws/tree/master/pawsx | {
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https://api.github.com/repos/huggingface/datasets/issues/361 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/361/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/361/comments | https://api.github.com/repos/huggingface/datasets/issues/361/events | https://github.com/huggingface/datasets/issues/361 | 653,757,376 | MDU6SXNzdWU2NTM3NTczNzY= | 361 | 🐛 [Metrics] ROUGE is non-deterministic | {
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"Hi, can you give a full self-contained example to reproduce this behavior?",
"> Hi, can you give a full self-contained example to reproduce this behavior?\r\n\r\nThere is a notebook in the post ;)",
"> If I run the ROUGE metric 2 times, with same predictions / references, the scores are slightly different.\r\n... | 2020-07-09T04:39:37 | 2022-09-09T15:20:55 | 2020-07-20T23:48:37 | NONE | null | null | null | null | If I run the ROUGE metric 2 times, with same predictions / references, the scores are slightly different.
Refer to [this Colab notebook](https://colab.research.google.com/drive/1wRssNXgb9ldcp4ulwj-hMJn0ywhDOiDy?usp=sharing) for reproducing the problem.
Example of F-score for ROUGE-1, ROUGE-2, ROUGE-L in 2 differe... | {
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https://api.github.com/repos/huggingface/datasets/issues/360 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/360/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/360/comments | https://api.github.com/repos/huggingface/datasets/issues/360/events | https://github.com/huggingface/datasets/issues/360 | 653,687,176 | MDU6SXNzdWU2NTM2ODcxNzY= | 360 | [Feature request] Add dataset.ragged_map() function for many-to-many transformations | {
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"Actually `map(batched=True)` can already change the size of the dataset.\r\nIt can accept examples of length `N` and returns a batch of length `M` (can be null or greater than `N`).\r\n\r\nI'll make that explicit in the doc that I'm currently writing.",
"You're two steps ahead of me :) In my testing, it also wor... | 2020-07-09T01:04:43 | 2020-07-09T19:31:51 | 2020-07-09T19:31:51 | CONTRIBUTOR | null | null | null | null | `dataset.map()` enables one-to-one transformations. Input one example and output one example. This is helpful for tokenizing and cleaning individual lines.
`dataset.filter()` enables one-to-(one-or-none) transformations. Input one example and output either zero/one example. This is helpful for removing portions from t... | {
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https://api.github.com/repos/huggingface/datasets/issues/359 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/359/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/359/comments | https://api.github.com/repos/huggingface/datasets/issues/359/events | https://github.com/huggingface/datasets/issues/359 | 653,656,279 | MDU6SXNzdWU2NTM2NTYyNzk= | 359 | ArrowBasedBuilder _prepare_split parse_schema breaks on nested structures | {
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"Hi, it depends on what it is in your `dataset_builder.py` file. Can you share it?\r\n\r\nIf you are just loading `json` files, you can also directly use the `json` script (which will find the schema/features from your JSON structure):\r\n\r\n```python\r\nfrom nlp import load_dataset\r\nds = load_dataset(\"json\", ... | 2020-07-08T23:24:05 | 2020-07-10T14:52:06 | 2020-07-10T14:52:06 | NONE | null | null | null | null | I tried using the Json dataloader to load some JSON lines files. but get an exception in the parse_schema function.
```
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-23-9aecfbee53bd> in <mo... | {
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https://api.github.com/repos/huggingface/datasets/issues/355 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/355/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/355/comments | https://api.github.com/repos/huggingface/datasets/issues/355/events | https://github.com/huggingface/datasets/issues/355 | 653,451,013 | MDU6SXNzdWU2NTM0NTEwMTM= | 355 | can't load SNLI dataset | {
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"I just added the processed files of `snli` on our google storage, so that when you do `load_dataset` it can download the processed files from there :)\r\n\r\nWe are thinking about having available those processed files for more datasets in the future, because sometimes files aren't available (like for `snli`), or ... | 2020-07-08T16:54:14 | 2020-07-18T05:15:57 | 2020-07-15T07:59:01 | CONTRIBUTOR | null | null | null | null | `nlp` seems to load `snli` from some URL based on nlp.stanford.edu. This subdomain is frequently down -- including right now, when I'd like to load `snli` in a Colab notebook, but can't.
Is there a plan to move these datasets to huggingface servers for a more stable solution?
Btw, here's the stack trace:
```
... | {
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https://api.github.com/repos/huggingface/datasets/issues/353 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/353/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/353/comments | https://api.github.com/repos/huggingface/datasets/issues/353/events | https://github.com/huggingface/datasets/issues/353 | 653,250,611 | MDU6SXNzdWU2NTMyNTA2MTE= | 353 | [Dataset requests] New datasets for Text Classification | {
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"Pinging @mariamabarham as well",
"- `nlp` has MR! It's called `rotten_tomatoes`\r\n- SST is part of GLUE, or is that just SST-2?\r\n- `nlp` also has `ag_news`, a popular news classification dataset\r\n\r\nI'd also like to see:\r\n- the Yahoo Answers topic classification dataset\r\n- the Kaggle Fake News classifi... | 2020-07-08T12:17:58 | 2025-04-05T09:28:15 | null | MEMBER | null | null | null | null | We are missing a few datasets for Text Classification which is an important field.
Namely, it would be really nice to add:
- [x] TREC-6 dataset (see here for instance: https://pytorchnlp.readthedocs.io/en/latest/source/torchnlp.datasets.html#torchnlp.datasets.trec_dataset) **[done]**
- #386
- [x] Yelp-5
- #... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/347 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/347/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/347/comments | https://api.github.com/repos/huggingface/datasets/issues/347/events | https://github.com/huggingface/datasets/issues/347 | 652,106,567 | MDU6SXNzdWU2NTIxMDY1Njc= | 347 | 'cp950' codec error from load_dataset('xtreme', 'tydiqa') | {
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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 ... | 2020-07-07T08:14:23 | 2020-09-07T14:51:45 | 2020-09-07T14:51:45 | CONTRIBUTOR | null | null | null | 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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https://api.github.com/repos/huggingface/datasets/issues/345 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/345/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/345/comments | https://api.github.com/repos/huggingface/datasets/issues/345/events | https://github.com/huggingface/datasets/issues/345 | 651,761,201 | MDU6SXNzdWU2NTE3NjEyMDE= | 345 | Supporting documents in ELI5 | {
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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... | 2020-07-06T19:14:13 | 2020-10-27T15:38:45 | 2020-10-27T15:38:45 | NONE | null | null | null | 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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https://api.github.com/repos/huggingface/datasets/issues/342 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/342/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/342/comments | https://api.github.com/repos/huggingface/datasets/issues/342/events | https://github.com/huggingface/datasets/issues/342 | 651,333,194 | MDU6SXNzdWU2NTEzMzMxOTQ= | 342 | Features should be updated when `map()` changes schema | {
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"`dataset.column_names` are being updated but `dataset.features` aren't indeed..."
] | 2020-07-06T08:03:23 | 2020-07-23T10:15:16 | 2020-07-23T10:15:16 | MEMBER | null | null | null | 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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https://api.github.com/repos/huggingface/datasets/issues/337 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/337/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/337/comments | https://api.github.com/repos/huggingface/datasets/issues/337/events | https://github.com/huggingface/datasets/issues/337 | 650,035,887 | MDU6SXNzdWU2NTAwMzU4ODc= | 337 | [Feature request] Export Arrow dataset to TFRecords | {
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```python
# use these existing methods
ds = load_dataset("wikitext", "wik... | {
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https://api.github.com/repos/huggingface/datasets/issues/336 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/336/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/336/comments | https://api.github.com/repos/huggingface/datasets/issues/336/events | https://github.com/huggingface/datasets/issues/336 | 649,914,203 | MDU6SXNzdWU2NDk5MTQyMDM= | 336 | [Dataset requests] New datasets for Open Question Answering | {
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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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https://api.github.com/repos/huggingface/datasets/issues/331 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/331/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/331/comments | https://api.github.com/repos/huggingface/datasets/issues/331/events | https://github.com/huggingface/datasets/issues/331 | 648,533,199 | MDU6SXNzdWU2NDg1MzMxOTk= | 331 | Loading CNN/Daily Mail dataset produces `nlp.utils.info_utils.NonMatchingSplitsSizesError` | {
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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... | 2020-06-30T22:21:33 | 2020-07-09T13:03:40 | 2020-07-09T13:03:40 | CONTRIBUTOR | null | null | null | 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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https://api.github.com/repos/huggingface/datasets/issues/329 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/329/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/329/comments | https://api.github.com/repos/huggingface/datasets/issues/329/events | https://github.com/huggingface/datasets/issues/329 | 648,446,979 | MDU6SXNzdWU2NDg0NDY5Nzk= | 329 | [Bug] FileLock dependency incompatible with filesystem | {
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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... | 2020-06-30T19:45:31 | 2024-12-26T15:13:39 | 2020-06-30T21:33:06 | CONTRIBUTOR | null | null | null | 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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https://api.github.com/repos/huggingface/datasets/issues/328 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/328/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/328/comments | https://api.github.com/repos/huggingface/datasets/issues/328/events | https://github.com/huggingface/datasets/issues/328 | 648,326,841 | MDU6SXNzdWU2NDgzMjY4NDE= | 328 | Fork dataset | {
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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... | 2020-06-30T16:42:53 | 2020-07-06T21:43:59 | 2020-07-06T21:43:59 | NONE | null | null | null | 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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https://api.github.com/repos/huggingface/datasets/issues/326 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/326/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/326/comments | https://api.github.com/repos/huggingface/datasets/issues/326/events | https://github.com/huggingface/datasets/issues/326 | 648,126,103 | MDU6SXNzdWU2NDgxMjYxMDM= | 326 | Large dataset in Squad2-format | {
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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 ... | 2020-06-30T12:18:59 | 2020-07-09T09:01:50 | 2020-07-09T09:01:50 | CONTRIBUTOR | null | null | null | 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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https://api.github.com/repos/huggingface/datasets/issues/324 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/324/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/324/comments | https://api.github.com/repos/huggingface/datasets/issues/324/events | https://github.com/huggingface/datasets/issues/324 | 647,525,725 | MDU6SXNzdWU2NDc1MjU3MjU= | 324 | Error when calculating glue score | {
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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... | 2020-06-29T16:53:48 | 2020-07-09T09:13:34 | 2020-07-09T09:13:34 | NONE | null | null | null | 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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https://api.github.com/repos/huggingface/datasets/issues/321 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/321/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/321/comments | https://api.github.com/repos/huggingface/datasets/issues/321/events | https://github.com/huggingface/datasets/issues/321 | 647,271,526 | MDU6SXNzdWU2NDcyNzE1MjY= | 321 | ERROR:root:mwparserfromhell | {
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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... | 2020-06-29T11:10:43 | 2022-02-14T15:21:46 | 2022-02-14T15:21:46 | NONE | null | null | null | 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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https://api.github.com/repos/huggingface/datasets/issues/320 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/320/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/320/comments | https://api.github.com/repos/huggingface/datasets/issues/320/events | https://github.com/huggingface/datasets/issues/320 | 647,188,167 | MDU6SXNzdWU2NDcxODgxNjc= | 320 | Blog Authorship Corpus, Non Matching Splits Sizes Error, nlp viewer | {
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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 `."
] | 2020-06-29T07:36:35 | 2020-06-29T14:44:42 | 2020-06-29T14:44:42 | CONTRIBUTOR | null | null | null | 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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https://api.github.com/repos/huggingface/datasets/issues/319 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/319/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/319/comments | https://api.github.com/repos/huggingface/datasets/issues/319/events | https://github.com/huggingface/datasets/issues/319 | 646,792,487 | MDU6SXNzdWU2NDY3OTI0ODc= | 319 | Nested sequences with dicts | {
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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 ... | 2020-06-27T23:45:17 | 2020-07-03T10:22:00 | 2020-07-03T10:22:00 | CONTRIBUTOR | null | null | null | 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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https://api.github.com/repos/huggingface/datasets/issues/317 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/317/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/317/comments | https://api.github.com/repos/huggingface/datasets/issues/317/events | https://github.com/huggingface/datasets/issues/317 | 646,555,384 | MDU6SXNzdWU2NDY1NTUzODQ= | 317 | Adding a dataset with multiple subtasks | {
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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... | 2020-06-26T23:14:19 | 2020-10-27T15:36:52 | 2020-10-27T15:36:52 | NONE | null | null | null | 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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https://api.github.com/repos/huggingface/datasets/issues/315 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/315/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/315/comments | https://api.github.com/repos/huggingface/datasets/issues/315/events | https://github.com/huggingface/datasets/issues/315 | 645,888,943 | MDU6SXNzdWU2NDU4ODg5NDM= | 315 | [Question] Best way to batch a large 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... | 2020-06-25T22:30:20 | 2020-10-27T15:38:17 | null | CONTRIBUTOR | null | null | null | 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(... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/312 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/312/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/312/comments | https://api.github.com/repos/huggingface/datasets/issues/312/events | https://github.com/huggingface/datasets/issues/312 | 645,025,561 | MDU6SXNzdWU2NDUwMjU1NjE= | 312 | [Feature request] Add `shard()` method to dataset | {
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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... | 2020-06-24T22:48:33 | 2020-07-06T12:35:36 | 2020-07-06T12:35:36 | CONTRIBUTOR | null | null | null | 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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https://api.github.com/repos/huggingface/datasets/issues/307 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/307/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/307/comments | https://api.github.com/repos/huggingface/datasets/issues/307/events | https://github.com/huggingface/datasets/issues/307 | 644,187,262 | MDU6SXNzdWU2NDQxODcyNjI= | 307 | Specify encoding for MRPC | {
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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/305 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/305/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/305/comments | https://api.github.com/repos/huggingface/datasets/issues/305/events | https://github.com/huggingface/datasets/issues/305 | 644,148,149 | MDU6SXNzdWU2NDQxNDgxNDk= | 305 | Importing downloaded package repository fails | {
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Currently however, the code seems to... | {
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https://api.github.com/repos/huggingface/datasets/issues/304 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/304/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/304/comments | https://api.github.com/repos/huggingface/datasets/issues/304/events | https://github.com/huggingface/datasets/issues/304 | 644,091,970 | MDU6SXNzdWU2NDQwOTE5NzA= | 304 | Problem while printing doc string when instantiating multiple metrics. | {
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Attached [Colab](https://colab.research.google.com/drive/13H0ZgyQ2se0mqJ2yyew0bNEgJuHaJ8H3?usp=sharing) Notebook for problem ... | {
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https://api.github.com/repos/huggingface/datasets/issues/302 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/302/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/302/comments | https://api.github.com/repos/huggingface/datasets/issues/302/events | https://github.com/huggingface/datasets/issues/302 | 643,910,418 | MDU6SXNzdWU2NDM5MTA0MTg= | 302 | Question - Sign Language Datasets | {
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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 \"... | 2020-06-23T14:53:40 | 2020-11-25T11:25:33 | 2020-11-25T11:25:33 | CONTRIBUTOR | null | null | null | 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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https://api.github.com/repos/huggingface/datasets/issues/301 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/301/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/301/comments | https://api.github.com/repos/huggingface/datasets/issues/301/events | https://github.com/huggingface/datasets/issues/301 | 643,763,525 | MDU6SXNzdWU2NDM3NjM1MjU= | 301 | Setting cache_dir gives error on wikipedia download | {
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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!"
] | 2020-06-23T11:31:44 | 2020-06-24T07:05:07 | 2020-06-24T07:05:07 | NONE | null | null | null | 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/297 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/297/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/297/comments | https://api.github.com/repos/huggingface/datasets/issues/297/events | https://github.com/huggingface/datasets/issues/297 | 643,444,625 | MDU6SXNzdWU2NDM0NDQ2MjU= | 297 | Error in Demo for Specific Datasets | {
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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... | 2020-06-23T00:38:42 | 2020-07-17T17:43:06 | 2020-07-17T17:43:06 | NONE | null | null | null | null | Selecting `natural_questions` or `newsroom` dataset in the online demo results in an error similar to the following.
| {
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https://api.github.com/repos/huggingface/datasets/issues/296 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/296/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/296/comments | https://api.github.com/repos/huggingface/datasets/issues/296/events | https://github.com/huggingface/datasets/issues/296 | 643,423,717 | MDU6SXNzdWU2NDM0MjM3MTc= | 296 | snli -1 labels | {
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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... | 2020-06-22T23:33:30 | 2020-06-23T14:41:59 | 2020-06-23T14:41:58 | CONTRIBUTOR | null | null | null | 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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https://api.github.com/repos/huggingface/datasets/issues/295 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/295/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/295/comments | https://api.github.com/repos/huggingface/datasets/issues/295/events | https://github.com/huggingface/datasets/issues/295 | 643,245,412 | MDU6SXNzdWU2NDMyNDU0MTI= | 295 | Improve input warning for evaluation metrics | {
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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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https://api.github.com/repos/huggingface/datasets/issues/294 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/294/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/294/comments | https://api.github.com/repos/huggingface/datasets/issues/294/events | https://github.com/huggingface/datasets/issues/294 | 643,181,179 | MDU6SXNzdWU2NDMxODExNzk= | 294 | Cannot load arxiv dataset on MacOS? | {
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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... | 2020-06-22T15:46:55 | 2020-06-30T15:25:10 | 2020-06-30T15:25:10 | CONTRIBUTOR | null | null | null | 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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https://api.github.com/repos/huggingface/datasets/issues/290 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/290/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/290/comments | https://api.github.com/repos/huggingface/datasets/issues/290/events | https://github.com/huggingface/datasets/issues/290 | 641,978,286 | MDU6SXNzdWU2NDE5NzgyODY= | 290 | ConnectionError - Eli5 dataset download | {
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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!"
] | 2020-06-19T13:40:33 | 2020-06-20T13:22:24 | 2020-06-20T13:22:24 | NONE | null | null | null | 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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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"
] | 2020-06-19T11:01:22 | 2020-06-21T09:05:11 | 2020-06-21T09:05:11 | NONE | null | null | null | 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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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/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... | 2020-06-18T09:47:27 | 2020-06-20T13:15:12 | 2020-06-20T13:15:12 | CONTRIBUTOR | null | null | null | 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... | 2020-06-17T17:17:21 | 2021-07-06T21:43:28 | 2021-04-18T23:43:49 | NONE | null | null | null | 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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https://api.github.com/repos/huggingface/datasets/issues/278 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/278/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/278/comments | https://api.github.com/repos/huggingface/datasets/issues/278/events | https://github.com/huggingface/datasets/issues/278 | 640,518,917 | MDU6SXNzdWU2NDA1MTg5MTc= | 278 | MemoryError when loading German Wikipedia | {
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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 ... | 2020-06-17T15:06:21 | 2020-06-19T12:53:02 | 2020-06-19T12:53:02 | NONE | null | null | null | 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. "
] | 2020-06-17T05:54:52 | 2020-06-21T00:21:45 | 2020-06-21T00:21:45 | CONTRIBUTOR | null | null | null | 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/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... | 2020-06-15T21:02:26 | 2020-07-06T15:35:02 | 2020-07-06T15:35:02 | CONTRIBUTOR | null | null | null | 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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"C4 is too large to be shown in the viewer"
] | 2020-06-13T08:26:16 | 2020-10-27T15:35:29 | 2020-10-27T15:35:13 | NONE | null | null | null | 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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"gists... | [] | 2020-06-13T06:26:54 | 2020-06-18T07:41:44 | 2020-06-18T07:41:44 | NONE | null | null | null | null | I'm running into an error using metrics for computation in the latest master as well as version 0.2.1. Here is a minimal example:
```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/267 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/267/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/267/comments | https://api.github.com/repos/huggingface/datasets/issues/267/events | https://github.com/huggingface/datasets/issues/267 | 637,415,545 | MDU6SXNzdWU2Mzc0MTU1NDU= | 267 | How can I load/find WMT en-romanian? | {
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"I will take a look :-) "
] | 2020-06-12T01:09:37 | 2020-06-19T08:24:19 | 2020-06-19T08:24:19 | CONTRIBUTOR | null | null | null | 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/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... | 2020-06-11T13:42:18 | 2022-02-10T13:26:35 | 2022-02-10T13:26:35 | CONTRIBUTOR | null | null | null | 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/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... | 2020-06-10T16:04:19 | 2020-06-11T14:35:12 | 2020-06-11T14:35:12 | NONE | null | null | null | 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/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... | 2020-06-10T13:18:13 | 2023-03-14T13:56:07 | 2020-06-18T22:20:24 | NONE | null | null | null | 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... | 2020-06-10T01:27:07 | 2020-06-10T12:46:34 | 2020-06-10T12:46:34 | CONTRIBUTOR | null | null | null | 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... | 2020-06-09T17:12:34 | 2020-06-10T21:45:32 | 2020-06-09T17:26:53 | NONE | null | null | null | 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... | 2020-06-09T16:38:12 | 2020-06-09T16:51:42 | 2020-06-09T16:51:42 | NONE | null | null | null | 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/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 "
] | 2020-06-09T02:22:13 | 2020-06-09T08:41:38 | 2020-06-09T08:41:38 | NONE | null | null | null | 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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https://api.github.com/repos/huggingface/datasets/issues/252 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/252/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/252/comments | https://api.github.com/repos/huggingface/datasets/issues/252/events | https://github.com/huggingface/datasets/issues/252 | 634,563,239 | MDU6SXNzdWU2MzQ1NjMyMzk= | 252 | NonMatchingSplitsSizesError error when reading the IMDB dataset | {
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"I just tried on my side and I didn't encounter your problem.\r\nApparently the script doesn't generate all the examples on your side.\r\n\r\nCan you provide the version of `nlp` you're using ?\r\nCan you try to clear your cache and re-run the code ?",
"I updated it, that was it, thanks!",
"Hello, I am facing t... | 2020-06-08T12:26:24 | 2021-08-27T15:20:58 | 2020-06-08T14:01:26 | NONE | null | null | null | null | Hi!
I am trying to load the `imdb` dataset with this line:
`dataset = nlp.load_dataset('imdb', data_dir='/A/PATH', cache_dir='/A/PATH')`
but I am getting the following error:
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
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https://api.github.com/repos/huggingface/datasets/issues/249 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/249/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/249/comments | https://api.github.com/repos/huggingface/datasets/issues/249/events | https://github.com/huggingface/datasets/issues/249 | 633,393,443 | MDU6SXNzdWU2MzMzOTM0NDM= | 249 | [Dataset created] some critical small issues when I was creating a dataset | {
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"Thanks for noticing all these :) They should be easy to fix indeed",
"Alright I think I fixed all the problems you mentioned. Thanks again, that will be useful for many people.\r\nThere is still more work needed for point 7. but we plan to have some nice docs soon."
] | 2020-06-07T12:58:54 | 2020-06-12T08:28:51 | 2020-06-12T08:28:51 | CONTRIBUTOR | null | null | null | null | Hi, I successfully created a dataset and has made a pr #248.
But I have encountered several problems when I was creating it, and those should be easy to fix.
1. Not found dataset_info.json
should be fixed by #241 , eager to wait it be merged.
2. Forced to install `apach_beam`
If we should install it, then it m... | {
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https://api.github.com/repos/huggingface/datasets/issues/246 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/246/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/246/comments | https://api.github.com/repos/huggingface/datasets/issues/246/events | https://github.com/huggingface/datasets/issues/246 | 632,380,054 | MDU6SXNzdWU2MzIzODAwNTQ= | 246 | What is the best way to cache a dataset? | {
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"Everything is already cached by default in 🤗nlp (in particular dataset\nloading and all the “map()” operations) so I don’t think you need to do any\nspecific caching in streamlit.\n\nTell us if you feel like it’s not the case.\n\nOn Sat, 6 Jun 2020 at 13:02, Fabrizio Milo <notifications@github.com> wrote:\n\n> Fo... | 2020-06-06T11:02:07 | 2020-07-09T09:15:07 | 2020-07-09T09:15:07 | NONE | null | null | null | null | For example if I want to use streamlit with a nlp dataset:
```
@st.cache
def load_data():
return nlp.load_dataset('squad')
```
This code raises the error "uncachable object"
Right now I just fixed with a constant for my specific case:
```
@st.cache(hash_funcs={pyarrow.lib.Buffer: lambda b: 0})
```... | {
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https://api.github.com/repos/huggingface/datasets/issues/245 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/245/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/245/comments | https://api.github.com/repos/huggingface/datasets/issues/245/events | https://github.com/huggingface/datasets/issues/245 | 631,985,108 | MDU6SXNzdWU2MzE5ODUxMDg= | 245 | SST-2 test labels are all -1 | {
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"this also happened to me with `nlp.load_dataset('glue', 'mnli')`",
"Yes, this is because the test sets for glue are hidden so the labels are\nnot publicly available. You can read the glue paper for more details.\n\nOn Sat, 6 Jun 2020 at 18:16, Jack Morris <notifications@github.com> wrote:\n\n> this also happened... | 2020-06-05T21:41:42 | 2021-12-08T00:47:32 | 2020-06-06T16:56:41 | CONTRIBUTOR | null | null | null | null | I'm trying to test a model on the SST-2 task, but all the labels I see in the test set are -1.
```
>>> import nlp
>>> glue = nlp.load_dataset('glue', 'sst2')
>>> glue
{'train': Dataset(schema: {'sentence': 'string', 'label': 'int64', 'idx': 'int32'}, num_rows: 67349), 'validation': Dataset(schema: {'sentence': 'st... | {
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https://api.github.com/repos/huggingface/datasets/issues/242 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/242/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/242/comments | https://api.github.com/repos/huggingface/datasets/issues/242/events | https://github.com/huggingface/datasets/issues/242 | 631,733,683 | MDU6SXNzdWU2MzE3MzM2ODM= | 242 | UnicodeDecodeError when downloading GLUE-MNLI | {
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"It should be good now, thanks for noticing and fixing it ! I would say that it was because you are on windows but not 100% sure",
"On Windows Python supports Unicode almost everywhere, but one of the notable exceptions is open() where it uses the locale encoding schema. So platform independent python scripts wou... | 2020-06-05T16:30:01 | 2020-06-09T16:06:47 | 2020-06-08T08:45:03 | CONTRIBUTOR | null | null | null | null | When I run
```python
dataset = nlp.load_dataset('glue', 'mnli')
```
I get an encoding error (could it be because I'm using Windows?) :
```python
# Lots of error log lines later...
~\Miniconda3\envs\nlp\lib\site-packages\tqdm\std.py in __iter__(self)
1128 try:
-> 1129 for obj in iterable:... | {
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https://api.github.com/repos/huggingface/datasets/issues/240 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/240/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/240/comments | https://api.github.com/repos/huggingface/datasets/issues/240/events | https://github.com/huggingface/datasets/issues/240 | 631,434,677 | MDU6SXNzdWU2MzE0MzQ2Nzc= | 240 | Deterministic dataset loading | {
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"Yes good point !",
"I think using `sorted(glob.glob())` would actually solve this problem. Can you think of other reasons why dataset loading might not be deterministic? @mariamabarham @yjernite @lhoestq @thomwolf . \r\n\r\nI can do a sweep through the dataset scripts and fix the glob.glob() if you guys are ok w... | 2020-06-05T09:03:26 | 2020-06-08T09:18:14 | 2020-06-08T09:18:14 | CONTRIBUTOR | null | null | null | null | When calling:
```python
import nlp
dataset = nlp.load_dataset("trivia_qa", split="validation[:1%]")
```
the resulting dataset is not deterministic over different google colabs.
After talking to @thomwolf, I suspect the reason to be the use of `glob.glob` in line:
https://github.com/huggingface/nlp/blob/2e0... | {
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https://api.github.com/repos/huggingface/datasets/issues/239 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/239/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/239/comments | https://api.github.com/repos/huggingface/datasets/issues/239/events | https://github.com/huggingface/datasets/issues/239 | 631,340,440 | MDU6SXNzdWU2MzEzNDA0NDA= | 239 | [Creating new dataset] Not found dataset_info.json | {
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"I think you can just `rm` this directory and it should be good :)",
"@lhoestq - this seems to happen quite often (already the 2nd issue). Can we maybe delete this automatically?",
"Yes I have an idea of what's going on. I'm sure I can fix that",
"Hi, I rebase my local copy to `fix-empty-cache-dir`, and try t... | 2020-06-05T06:15:04 | 2020-06-07T13:01:04 | 2020-06-07T13:01:04 | CONTRIBUTOR | null | null | null | null | Hi, I am trying to create Toronto Book Corpus. #131
I ran
`~/nlp % python nlp-cli test datasets/bookcorpus --save_infos --all_configs`
but this doesn't create `dataset_info.json` and try to use it
```
INFO:nlp.load:Checking datasets/bookcorpus/bookcorpus.py for additional imports.
INFO:filelock:Lock 1397953257... | {
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https://api.github.com/repos/huggingface/datasets/issues/238 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/238/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/238/comments | https://api.github.com/repos/huggingface/datasets/issues/238/events | https://github.com/huggingface/datasets/issues/238 | 631,260,143 | MDU6SXNzdWU2MzEyNjAxNDM= | 238 | [Metric] Bertscore : Warning : Empty candidate sentence; Setting recall to be 0. | {
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"description": "A bug in a metric script",
"id": 2067393914,
"name": "metric bug",
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"This print statement comes from the official implementation of bert_score (see [here](https://github.com/Tiiiger/bert_score/blob/master/bert_score/utils.py#L343)). The warning shows up only if the attention mask outputs no candidate.\r\nRight now we want to only use official code for metrics to have fair evaluatio... | 2020-06-05T02:14:47 | 2020-06-29T17:10:19 | 2020-06-29T17:10:19 | NONE | null | null | null | null | When running BERT-Score, I'm meeting this warning :
> Warning: Empty candidate sentence; Setting recall to be 0.
Code :
```
import nlp
metric = nlp.load_metric("bertscore")
scores = metric.compute(["swag", "swags"], ["swags", "totally something different"], lang="en", device=0)
```
---
**What am I do... | {
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https://api.github.com/repos/huggingface/datasets/issues/237 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/237/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/237/comments | https://api.github.com/repos/huggingface/datasets/issues/237/events | https://github.com/huggingface/datasets/issues/237 | 631,199,940 | MDU6SXNzdWU2MzExOTk5NDA= | 237 | Can't download MultiNLI | {
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"You should use `load_dataset('glue', 'mnli')`",
"Thanks! I thought I had to use the same code displayed in the live viewer:\r\n```python\r\n!pip install nlp\r\nfrom nlp import load_dataset\r\ndataset = load_dataset('multi_nli', 'plain_text')\r\n```\r\nYour suggestion works, even if then I got a different issue (... | 2020-06-04T23:05:21 | 2020-06-06T10:51:34 | 2020-06-06T10:51:34 | CONTRIBUTOR | null | null | null | null | When I try to download MultiNLI with
```python
dataset = load_dataset('multi_nli')
```
I get this long error:
```python
---------------------------------------------------------------------------
OSError Traceback (most recent call last)
<ipython-input-13-3b11f6be4cb9> in <m... | {
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https://api.github.com/repos/huggingface/datasets/issues/234 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/234/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/234/comments | https://api.github.com/repos/huggingface/datasets/issues/234/events | https://github.com/huggingface/datasets/issues/234 | 630,534,427 | MDU6SXNzdWU2MzA1MzQ0Mjc= | 234 | Huggingface NLP, Uploading custom dataset | {
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"What do you mean 'custom' ? You may want to elaborate on it when ask a question.\r\n\r\nAnyway, there are two things you may interested\r\n`nlp.Dataset.from_file` and `load_dataset(..., cache_dir=)`",
"To load a dataset you need to have a script that defines the format of the examples, the splits and the way to ... | 2020-06-04T05:59:06 | 2020-07-06T09:33:26 | 2020-07-06T09:33:26 | NONE | null | null | null | null | Hello,
Does anyone know how we can call our custom dataset using the nlp.load command? Let's say that I have a dataset based on the same format as that of squad-v1.1, how am I supposed to load it using huggingface nlp.
Thank you! | {
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https://api.github.com/repos/huggingface/datasets/issues/233 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/233/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/233/comments | https://api.github.com/repos/huggingface/datasets/issues/233/events | https://github.com/huggingface/datasets/issues/233 | 630,432,132 | MDU6SXNzdWU2MzA0MzIxMzI= | 233 | Fail to download c4 english corpus | {
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"Hello ! Thanks for noticing this bug, let me fix that.\r\n\r\nAlso for information, as specified in the changelog of the latest release, C4 currently needs to have a runtime for apache beam to work on. Apache beam is used to process this very big dataset and it can work on dataflow, spark, flink, apex, etc. You ca... | 2020-06-04T01:06:38 | 2021-01-08T07:17:32 | 2020-06-08T09:16:59 | NONE | null | null | null | null | i run following code to download c4 English corpus.
```
dataset = nlp.load_dataset('c4', 'en', beam_runner='DirectRunner'
, data_dir='/mypath')
```
and i met failure as follows
```
Downloading and preparing dataset c4/en (download: Unknown size, generated: Unknown size, total: Unknown size) to /home/adam/.... | {
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https://api.github.com/repos/huggingface/datasets/issues/228 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/228/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/228/comments | https://api.github.com/repos/huggingface/datasets/issues/228/events | https://github.com/huggingface/datasets/issues/228 | 629,952,402 | MDU6SXNzdWU2Mjk5NTI0MDI= | 228 | Not able to access the XNLI dataset | {
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"Added pull request to change the name of the file from dataset_infos.json to dataset_info.json",
"Thanks for reporting this bug !\r\nAs it seems to be just a cache problem, I closed your PR.\r\nI think we might just need to clear and reload the `xnli` cache @srush ? ",
"Update: The dataset_info.json error is g... | 2020-06-03T12:25:14 | 2020-07-17T17:44:22 | 2020-07-17T17:44:22 | NONE | null | null | null | null | When I try to access the XNLI dataset, I get the following error. The option of plain_text get selected automatically and then I get the following error.
```
FileNotFoundError: [Errno 2] No such file or directory: '/home/sasha/.cache/huggingface/datasets/xnli/plain_text/1.0.0/dataset_info.json'
Traceback:
File "/... | {
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