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https://api.github.com/repos/huggingface/datasets/issues/1895 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1895/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1895/comments | https://api.github.com/repos/huggingface/datasets/issues/1895/events | https://github.com/huggingface/datasets/issues/1895 | 809,630,271 | MDU6SXNzdWU4MDk2MzAyNzE= | 1,895 | Bug Report: timestamp[ns] not recognized | {
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"Thanks for reporting !\r\n\r\nYou're right, `string_to_arrow` should be able to take `\"timestamp[ns]\"` as input and return the right pyarrow timestamp type.\r\nFeel free to suggest a fix for `string_to_arrow` and open a PR if you want to contribute ! This would be very appreciated :)\r\n\r\nTo give you more cont... | 1,613,507,884,000 | 1,613,759,231,000 | 1,613,759,231,000 | CONTRIBUTOR | null | Repro:
```
from datasets import Dataset
import pandas as pd
import pyarrow
df = pd.DataFrame(pd.date_range("2018-01-01", periods=3, freq="H"))
pyarrow.Table.from_pandas(df)
Dataset.from_pandas(df)
# Throws ValueError: Neither timestamp[ns] nor timestamp[ns]_ seems to be a pyarrow data type.
```
The fact... | {
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https://api.github.com/repos/huggingface/datasets/issues/1894 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1894/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1894/comments | https://api.github.com/repos/huggingface/datasets/issues/1894/events | https://github.com/huggingface/datasets/issues/1894 | 809,609,654 | MDU6SXNzdWU4MDk2MDk2NTQ= | 1,894 | benchmarking against MMapIndexedDataset | {
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"Hi sam !\r\nIndeed we can expect the performances to be very close since both MMapIndexedDataset and the `datasets` implem use memory mapping. With memory mapping what determines the I/O performance is the speed of your hard drive/SSD.\r\n\r\nIn terms of performance we're pretty close to the optimal speed for read... | 1,613,505,898,000 | 1,613,587,948,000 | null | MEMBER | null | I am trying to benchmark my datasets based implementation against fairseq's [`MMapIndexedDataset`](https://github.com/pytorch/fairseq/blob/master/fairseq/data/indexed_dataset.py#L365) and finding that, according to psrecord, my `datasets` implem uses about 3% more CPU memory and runs 1% slower for `wikitext103` (~1GB o... | {
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https://api.github.com/repos/huggingface/datasets/issues/1893 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1893/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1893/comments | https://api.github.com/repos/huggingface/datasets/issues/1893/events | https://github.com/huggingface/datasets/issues/1893 | 809,556,503 | MDU6SXNzdWU4MDk1NTY1MDM= | 1,893 | wmt19 is broken | {
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"This was also mentioned in https://github.com/huggingface/datasets/issues/488 \r\n\r\nThe bucket where is data was stored seems to be unavailable now. Maybe we can change the URL to the ones in https://conferences.unite.un.org/uncorpus/en/downloadoverview ?",
"Closing since this has been fixed by #1912"
] | 1,613,500,798,000 | 1,614,793,322,000 | 1,614,793,322,000 | CONTRIBUTOR | null | 1. Check which lang pairs we have: `--dataset_name wmt19`:
Please pick one among the available configs: ['cs-en', 'de-en', 'fi-en', 'gu-en', 'kk-en', 'lt-en', 'ru-en', 'zh-en', 'fr-de']
2. OK, let's pick `ru-en`:
`--dataset_name wmt19 --dataset_config "ru-en"`
no cookies:
```
Traceback (most recent c... | {
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https://api.github.com/repos/huggingface/datasets/issues/1892 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1892/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1892/comments | https://api.github.com/repos/huggingface/datasets/issues/1892/events | https://github.com/huggingface/datasets/issues/1892 | 809,554,174 | MDU6SXNzdWU4MDk1NTQxNzQ= | 1,892 | request to mirror wmt datasets, as they are really slow to download | {
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"Yes that would be awesome. Not only the download speeds are awful, but also some files are missing.\r\nWe list all the URLs in the datasets/wmt19/wmt_utils.py so we can make a script to download them all and host on S3.\r\nAlso I think most of the materials are under the CC BY-NC-SA 3.0 license (must double check)... | 1,613,500,571,000 | 1,635,231,342,000 | 1,616,673,203,000 | CONTRIBUTOR | null | Would it be possible to mirror the wmt data files under hf? Some of them take hours to download and not because of the local speed. They are all quite small datasets, just extremely slow to download.
Thank you! | {
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https://api.github.com/repos/huggingface/datasets/issues/1891 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1891/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1891/comments | https://api.github.com/repos/huggingface/datasets/issues/1891/events | https://github.com/huggingface/datasets/issues/1891 | 809,550,001 | MDU6SXNzdWU4MDk1NTAwMDE= | 1,891 | suggestion to improve a missing dataset error | {
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```
True, predict_with_generate=True)
Traceback (most recent call last):
... | {
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https://api.github.com/repos/huggingface/datasets/issues/1877 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1877/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1877/comments | https://api.github.com/repos/huggingface/datasets/issues/1877/events | https://github.com/huggingface/datasets/issues/1877 | 808,462,272 | MDU6SXNzdWU4MDg0NjIyNzI= | 1,877 | Allow concatenation of both in-memory and on-disk datasets | {
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"I started working on this. My idea is to first add the pyarrow Table wrappers InMemoryTable and MemoryMappedTable that both implement what's necessary regarding copy/pickle. Then have another wrapper that takes the concatenation of InMemoryTable/MemoryMappedTable objects.\r\n\r\nWhat's important here is that conca... | 1,613,389,186,000 | 1,616,777,518,000 | 1,616,777,518,000 | MEMBER | null | This is a prerequisite for the addition of the `add_item` feature (see #1870).
Currently there is one assumption that we would need to change: a dataset is either fully in memory (dataset._data_files is empty), or the dataset can be reloaded from disk (using the dataset._data_files).
This assumption is used for pickl... | {
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https://api.github.com/repos/huggingface/datasets/issues/1876 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1876/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1876/comments | https://api.github.com/repos/huggingface/datasets/issues/1876/events | https://github.com/huggingface/datasets/issues/1876 | 808,025,859 | MDU6SXNzdWU4MDgwMjU4NTk= | 1,876 | load_dataset("multi_woz_v22") NonMatchingChecksumError | {
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"Thanks for reporting !\r\nThis is due to the changes made in the data files in the multiwoz repo: https://github.com/budzianowski/multiwoz/pull/59\r\nI'm opening a PR to update the checksums of the data files.",
"I just merged the fix. It will be available in the new release of `datasets` later today.\r\nYou'll ... | 1,613,330,088,000 | 1,628,100,480,000 | 1,628,100,480,000 | NONE | null | Hi, it seems that loading the multi_woz_v22 dataset gives a NonMatchingChecksumError.
To reproduce:
`dataset = load_dataset('multi_woz_v22','v2.2_active_only',split='train')`
This will give the following error:
```
raise NonMatchingChecksumError(error_msg + str(bad_urls))
datasets.utils.info_utils.N... | {
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https://api.github.com/repos/huggingface/datasets/issues/1872 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1872/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1872/comments | https://api.github.com/repos/huggingface/datasets/issues/1872/events | https://github.com/huggingface/datasets/issues/1872 | 807,711,935 | MDU6SXNzdWU4MDc3MTE5MzU= | 1,872 | Adding a new column to the dataset after set_format was called | {
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"Hi ! Indeed if you add a column to a formatted dataset, then the new dataset gets a new formatting in which:\r\n```\r\nnew formatted columns = (all columns - previously unformatted columns)\r\n```\r\nTherefore the new column is going to be formatted using the `torch` formatting.\r\n\r\nIf you want your new column ... | 1,613,207,675,000 | 1,617,112,905,000 | 1,617,112,905,000 | NONE | null | Hi,
thanks for the nice library. I'm in the process of creating a custom dataset, which has a mix of tensors and lists of strings. I stumbled upon an error and want to know if its a problem on my side.
I load some lists of strings and integers, then call `data.set_format("torch", columns=["some_integer_column1"... | {
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https://api.github.com/repos/huggingface/datasets/issues/1867 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1867/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1867/comments | https://api.github.com/repos/huggingface/datasets/issues/1867/events | https://github.com/huggingface/datasets/issues/1867 | 807,127,181 | MDU6SXNzdWU4MDcxMjcxODE= | 1,867 | ERROR WHEN USING SET_TRANSFORM() | {
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"Hi @alejandrocros it looks like an incompatibility with the current Trainer @sgugger \r\nIndeed currently the Trainer of `transformers` doesn't support a dataset with a transform\r\n\r\nIt looks like it comes from this line: https://github.com/huggingface/transformers/blob/f51188cbe74195c14c5b3e2e8f10c2f435f9751a/... | 1,613,126,311,000 | 1,614,607,464,000 | 1,614,168,043,000 | NONE | null | Hi, I'm trying to use dataset.set_transform(encode) as @lhoestq told me in this issue: https://github.com/huggingface/datasets/issues/1825#issuecomment-774202797
However, when I try to use Trainer from transformers with such dataset, it throws an error:
```
TypeError: __init__() missing 1 required positional arg... | {
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https://api.github.com/repos/huggingface/datasets/issues/1864 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1864/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1864/comments | https://api.github.com/repos/huggingface/datasets/issues/1864/events | https://github.com/huggingface/datasets/issues/1864 | 806,172,843 | MDU6SXNzdWU4MDYxNzI4NDM= | 1,864 | Add Winogender Schemas | {
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"Nevermind, this one is already available on the hub under the name `'wino_bias'`: https://huggingface.co/datasets/wino_bias"
] | 1,613,031,518,000 | 1,613,031,591,000 | 1,613,031,591,000 | NONE | null | ## Adding a Dataset
- **Name:** Winogender Schemas
- **Description:** Winogender Schemas (inspired by Winograd Schemas) are minimal pairs of sentences that differ only by the gender of one pronoun in the sentence, designed to test for the presence of gender bias in automated coreference resolution systems.
- **Paper... | {
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https://api.github.com/repos/huggingface/datasets/issues/1863 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1863/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1863/comments | https://api.github.com/repos/huggingface/datasets/issues/1863/events | https://github.com/huggingface/datasets/issues/1863 | 806,171,311 | MDU6SXNzdWU4MDYxNzEzMTE= | 1,863 | Add WikiCREM | {
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"Hi @NielsRogge I would like to work on this dataset.\r\n\r\nThanks!",
"Hi @udapy, are you working on this?"
] | 1,613,031,360,000 | 1,615,102,033,000 | null | NONE | null | ## Adding a Dataset
- **Name:** WikiCREM
- **Description:** A large unsupervised corpus for coreference resolution.
- **Paper:** https://arxiv.org/abs/1905.06290
- **Github repo:**: https://github.com/vid-koci/bert-commonsense
- **Data:** https://ora.ox.ac.uk/objects/uuid:c83e94bb-7584-41a1-aef9-85b0e764d9e3
- **... | {
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https://api.github.com/repos/huggingface/datasets/issues/1859 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1859/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1859/comments | https://api.github.com/repos/huggingface/datasets/issues/1859/events | https://github.com/huggingface/datasets/issues/1859 | 805,479,025 | MDU6SXNzdWU4MDU0NzkwMjU= | 1,859 | Error "in void don't know how to serialize this type of index" when saving index to disk when device=0 (GPU) | {
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"Hi @corticalstack ! Thanks for reporting. Indeed in the recent versions of Faiss we must use `getDevice` to check if the index in on GPU.\r\n\r\nI'm opening a PR",
"I fixed this issue. It should work fine now.\r\nFeel free to try it out by installing `datasets` from source.\r\nOtherwise you can wait for the next... | 1,612,960,860,000 | 1,612,981,932,000 | 1,612,981,067,000 | NONE | null | Error serializing faiss index. Error as follows:
`Error in void faiss::write_index(const faiss::Index*, faiss::IOWriter*) at /home/conda/feedstock_root/build_artifacts/faiss-split_1612472484670/work/faiss/impl/index_write.cpp:453: don't know how to serialize this type of index`
Note:
`torch.cuda.is_availabl... | {
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https://api.github.com/repos/huggingface/datasets/issues/1857 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1857/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1857/comments | https://api.github.com/repos/huggingface/datasets/issues/1857/events | https://github.com/huggingface/datasets/issues/1857 | 805,391,107 | MDU6SXNzdWU4MDUzOTExMDc= | 1,857 | Unable to upload "community provided" dataset - 400 Client Error | {
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"Hi ! We're in the process of switching the community datasets to git repos, exactly like what we're doing for models.\r\nYou can find an example here:\r\nhttps://huggingface.co/datasets/lhoestq/custom_squad/tree/main\r\n\r\nWe'll update the CLI in the coming days and do a new release :)\r\n\r\nAlso cc @julien-c ma... | 1,612,953,541,000 | 1,627,967,173,000 | 1,627,967,173,000 | CONTRIBUTOR | null | Hi,
i'm trying to a upload a dataset as described [here](https://huggingface.co/docs/datasets/v1.2.0/share_dataset.html#sharing-a-community-provided-dataset). This is what happens:
```
$ datasets-cli login
$ datasets-cli upload_dataset my_dataset
About to upload file /path/to/my_dataset/dataset_infos.json to S3... | {
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https://api.github.com/repos/huggingface/datasets/issues/1856 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1856/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1856/comments | https://api.github.com/repos/huggingface/datasets/issues/1856/events | https://github.com/huggingface/datasets/issues/1856 | 805,360,200 | MDU6SXNzdWU4MDUzNjAyMDA= | 1,856 | load_dataset("amazon_polarity") NonMatchingChecksumError | {
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"Hi ! This issue may be related to #996 \r\nThis comes probably from the Quota Exceeded error from Google Drive.\r\nCan you try again tomorrow and see if you still have the error ?\r\n\r\nOn my side I didn't get any error today with `load_dataset(\"amazon_polarity\")`",
"+1 encountering this issue as well",
"@l... | 1,612,951,256,000 | 1,626,872,391,000 | null | NONE | null | Hi, it seems that loading the amazon_polarity dataset gives a NonMatchingChecksumError.
To reproduce:
```
load_dataset("amazon_polarity")
```
This will give the following error:
```
---------------------------------------------------------------------------
NonMatchingChecksumError Traceback ... | {
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https://api.github.com/repos/huggingface/datasets/issues/1854 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1854/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1854/comments | https://api.github.com/repos/huggingface/datasets/issues/1854/events | https://github.com/huggingface/datasets/issues/1854 | 805,204,397 | MDU6SXNzdWU4MDUyMDQzOTc= | 1,854 | Feature Request: Dataset.add_item | {
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"Hi @sshleifer.\r\n\r\nI am not sure of understanding the need of the `add_item` approach...\r\n\r\nBy just reading your \"Desired API\" section, I would say you could (nearly) get it with a 1-column Dataset:\r\n```python\r\ndata = {\"input_ids\": [np.array([4,4,2]), np.array([8,6,5,5,2]), np.array([3,3,31,5])]}\r\... | 1,612,937,160,000 | 1,619,172,090,000 | 1,619,172,090,000 | MEMBER | null | I'm trying to integrate `huggingface/datasets` functionality into `fairseq`, which requires (afaict) being able to build a dataset through an `add_item` method, such as https://github.com/pytorch/fairseq/blob/master/fairseq/data/indexed_dataset.py#L318, as opposed to loading all the text into arrow, and then `dataset.m... | {
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https://api.github.com/repos/huggingface/datasets/issues/1849 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1849/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1849/comments | https://api.github.com/repos/huggingface/datasets/issues/1849/events | https://github.com/huggingface/datasets/issues/1849 | 804,292,971 | MDU6SXNzdWU4MDQyOTI5NzE= | 1,849 | Add TIMIT | {
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"@patrickvonplaten Could you please help me with how the output text has to be represented in the data? TIMIT has Words, Phonemes and texts. Also has lot on info on the speaker and the dialect. Could you please help me? An example of how to arrange it would be super helpful!\r\n\r\n",
"Hey @vrindaprabhu - sure I'... | 1,612,855,781,000 | 1,615,787,977,000 | 1,615,787,977,000 | MEMBER | null | ## Adding a Dataset
- **Name:** *TIMIT*
- **Description:** *The TIMIT corpus of read speech has been designed to provide speech data for the acquisition of acoustic-phonetic knowledge and for the development and evaluation of automatic speech recognition systems*
- **Paper:** *Homepage*: http://groups.inf.ed.ac.uk... | {
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https://api.github.com/repos/huggingface/datasets/issues/1844 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1844/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1844/comments | https://api.github.com/repos/huggingface/datasets/issues/1844/events | https://github.com/huggingface/datasets/issues/1844 | 803,588,125 | MDU6SXNzdWU4MDM1ODgxMjU= | 1,844 | Update Open Subtitles corpus with original sentence IDs | {
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"Hi ! You're right this can can useful.\r\nThis should be easy to add, so feel free to give it a try if you want to contribute :)\r\nI think we just need to add it to the _generate_examples method of the OpenSubtitles dataset builder [here](https://github.com/huggingface/datasets/blob/master/datasets/open_subtitles... | 1,612,792,513,000 | 1,613,151,538,000 | 1,613,151,538,000 | CONTRIBUTOR | null | Hi! It would be great if you could add the original sentence ids to [Open Subtitles](https://huggingface.co/datasets/open_subtitles).
I can think of two reasons: first, it's possible to gather sentences for an entire document (the original ids contain media id, subtitle file id and sentence id), therefore somewhat a... | {
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"Hi @patrickvonplaten I would like to work on this dataset. \r\n\r\nThanks! ",
"That's awesome! Actually, I just noticed that this dataset might become a bit too big!\r\n\r\nMuST-C is the main dataset used for IWSLT19 and should probably be added as a standalone dataset. Would you be interested also in adding `d... | 1,612,790,865,000 | 1,621,004,014,000 | null | MEMBER | null | ## Adding a Dataset
- **Name:** *IWSLT19*
- **Description:** *The Speech Translation Task addresses the translation of English audio into German and Portuguese text.*
- **Hompage:** *https://sites.google.com/view/iwslt-evaluation-2019/speech-translation*
- **Data:** *https://sites.google.com/view/iwslt-evaluation-2... | {
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- **Name:** *AMI*
- **Description:** *The AMI Meeting Corpus is a multi-modal data set consisting of 100 hours of meeting recordings. For a gentle introduction to the corpus, see the corpus overview. To access the data, follow the directions given there. Around two-thirds of the data has been elic... | {
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- **Name:** *ljspeech*
- **Description:** *This is a public domain speech dataset consisting of 13,100 short audio clips of a single speaker reading passages from 7 non-fiction books. A transcription is provided for each clip. Clips vary in length from 1 to 10 seconds and have a total length of ap... | {
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https://api.github.com/repos/huggingface/datasets/issues/1840 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1840/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1840/comments | https://api.github.com/repos/huggingface/datasets/issues/1840/events | https://github.com/huggingface/datasets/issues/1840 | 803,560,039 | MDU6SXNzdWU4MDM1NjAwMzk= | 1,840 | Add common voice | {
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"I have started working on adding this dataset.",
"Hey @BirgerMoell - awesome that you started working on Common Voice. Common Voice is a bit special since, there is no direct download link to download the data. In these cases we usually consider two options:\r\n\r\n1) Find a hacky solution to extract the downloa... | 1,612,790,465,000 | 1,632,474,311,000 | 1,615,787,781,000 | MEMBER | null | ## Adding a Dataset
- **Name:** *common voice*
- **Description:** *Mozilla Common Voice Dataset*
- **Paper:** Homepage: https://voice.mozilla.org/en/datasets
- **Data:** https://voice.mozilla.org/en/datasets
- **Motivation:** Important speech dataset
- **TFDatasets Implementation**: https://www.tensorflow.org/dat... | {
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https://api.github.com/repos/huggingface/datasets/issues/1839 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1839/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1839/comments | https://api.github.com/repos/huggingface/datasets/issues/1839/events | https://github.com/huggingface/datasets/issues/1839 | 803,559,164 | MDU6SXNzdWU4MDM1NTkxNjQ= | 1,839 | Add Voxforge | {
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... | open | false | null | [] | null | [] | 1,612,790,396,000 | 1,612,790,911,000 | null | MEMBER | null | ## Adding a Dataset
- **Name:** *voxforge*
- **Description:** *VoxForge is a language classification dataset. It consists of user submitted audio clips submitted to the website. In this release, data from 6 languages is collected - English, Spanish, French, German, Russian, and Italian. Since the website is constant... | {
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https://api.github.com/repos/huggingface/datasets/issues/1838 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1838/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1838/comments | https://api.github.com/repos/huggingface/datasets/issues/1838/events | https://github.com/huggingface/datasets/issues/1838 | 803,557,521 | MDU6SXNzdWU4MDM1NTc1MjE= | 1,838 | Add tedlium | {
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"Hi @patrickvonplaten \r\nI can have a look to this dataset later since I am trying to add the OpenSLR dataset https://github.com/huggingface/datasets/pull/2173\r\nHopefully I have enough space since the compressed file is 21GB. The release 3 is even bigger: 54GB :-0"
] | 1,612,790,272,000 | 1,617,983,861,000 | null | MEMBER | null | ## Adding a Dataset
- **Name:** *tedlium*
- **Description:** *The TED-LIUM 1-3 corpus is English-language TED talks, with transcriptions, sampled at 16kHz. It contains about 118 hours of speech.*
- **Paper:** Homepage: http://www.openslr.org/7/, https://lium.univ-lemans.fr/en/ted-lium2/ &, https://www.openslr.org/51... | {
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https://api.github.com/repos/huggingface/datasets/issues/1837 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1837/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1837/comments | https://api.github.com/repos/huggingface/datasets/issues/1837/events | https://github.com/huggingface/datasets/issues/1837 | 803,555,650 | MDU6SXNzdWU4MDM1NTU2NTA= | 1,837 | Add VCTK | {
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"@patrickvonplaten I'd like to take this, if nobody has already done it. I have added datasets before through the datasets sprint, but I feel rusty on the details, so I'll look at the guide as well as similar audio PRs (#1878 in particular comes to mind). If there is any detail I should be aware of please, let me k... | 1,612,790,128,000 | 1,636,443,541,000 | null | MEMBER | null | ## Adding a Dataset
- **Name:** *VCTK*
- **Description:** *This CSTR VCTK Corpus includes speech data uttered by 110 English speakers with various accents. Each speaker reads out about 400 sentences, which were selected from a newspaper, the rainbow passage and an elicitation paragraph used for the speech accent arch... | {
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https://api.github.com/repos/huggingface/datasets/issues/1836 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1836/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1836/comments | https://api.github.com/repos/huggingface/datasets/issues/1836/events | https://github.com/huggingface/datasets/issues/1836 | 803,531,837 | MDU6SXNzdWU4MDM1MzE4Mzc= | 1,836 | test.json has been removed from the limit dataset repo (breaks dataset) | {
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"Thanks for the heads up ! I'm opening a PR to fix that"
] | 1,612,788,353,000 | 1,612,973,698,000 | 1,612,973,698,000 | NONE | null | https://github.com/huggingface/datasets/blob/16042b233dbff2a7585110134e969204c69322c3/datasets/limit/limit.py#L51
The URL is not valid anymore since test.json has been removed in master for some reason. Directly referencing the last commit works:
`https://raw.githubusercontent.com/ilmgut/limit_dataset/0707d3989cd... | {
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https://api.github.com/repos/huggingface/datasets/issues/1835 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1835/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1835/comments | https://api.github.com/repos/huggingface/datasets/issues/1835/events | https://github.com/huggingface/datasets/issues/1835 | 803,524,790 | MDU6SXNzdWU4MDM1MjQ3OTA= | 1,835 | Add CHiME4 dataset | {
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... | open | false | null | [] | null | [] | 1,612,787,798,000 | 1,612,790,011,000 | null | MEMBER | null | ## Adding a Dataset
- **Name:** Chime4
- **Description:** Chime4 is a dataset for automatic speech recognition. It is especially useful for evaluating models in a noisy environment and for multi-channel ASR
- **Paper:** Dataset comes from a channel: http://spandh.dcs.shef.ac.uk/chime_challenge/CHiME4/ . Results pape... | {
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https://api.github.com/repos/huggingface/datasets/issues/1832 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1832/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1832/comments | https://api.github.com/repos/huggingface/datasets/issues/1832/events | https://github.com/huggingface/datasets/issues/1832 | 802,880,897 | MDU6SXNzdWU4MDI4ODA4OTc= | 1,832 | Looks like nokogumbo is up-to-date now, so this is no longer needed. | {
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__Originally posted by @dependabot in https://github.com/discourse/discourse/pull/11373#issuecomment-738993432__ | {
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https://api.github.com/repos/huggingface/datasets/issues/1831 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1831/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1831/comments | https://api.github.com/repos/huggingface/datasets/issues/1831/events | https://github.com/huggingface/datasets/issues/1831 | 802,868,854 | MDU6SXNzdWU4MDI4Njg4NTQ= | 1,831 | Some question about raw dataset download info in the project . | {
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"Hi ! The `dl_manager` is a `DownloadManager` object and is responsible for downloading the raw data files.\r\nIt is used by dataset builders in their `_split_generators` method to download the raw data files that are necessary to build the datasets splits.\r\n\r\nThe `Conll2003` class is a dataset builder, and so ... | 1,612,676,016,000 | 1,614,262,218,000 | 1,614,262,218,000 | NONE | null | Hi , i review the code in
https://github.com/huggingface/datasets/blob/master/datasets/conll2003/conll2003.py
in the _split_generators function is the truly logic of download raw datasets with dl_manager
and use Conll2003 cls by use import_main_class in load_dataset function
My question is that , with this logic i... | {
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https://api.github.com/repos/huggingface/datasets/issues/1830 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1830/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1830/comments | https://api.github.com/repos/huggingface/datasets/issues/1830/events | https://github.com/huggingface/datasets/issues/1830 | 802,790,075 | MDU6SXNzdWU4MDI3OTAwNzU= | 1,830 | using map on loaded Tokenizer 10x - 100x slower than default Tokenizer? | {
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"Hi @wumpusman \r\n`datasets` has a caching mechanism that allows to cache the results of `.map` so that when you want to re-run it later it doesn't recompute it again.\r\nSo when you do `.map`, what actually happens is:\r\n1. compute the hash used to identify your `map` for the cache\r\n2. apply your function on e... | 1,612,645,226,000 | 1,614,203,774,000 | null | NONE | null | This could total relate to me misunderstanding particular call functions, but I added words to a GPT2Tokenizer, and saved it to disk (note I'm only showing snippets but I can share more) and the map function ran much slower:
````
def save_tokenizer(original_tokenizer,text,path="simpledata/tokenizer"):
words_u... | {
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https://api.github.com/repos/huggingface/datasets/issues/1827 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1827/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1827/comments | https://api.github.com/repos/huggingface/datasets/issues/1827/events | https://github.com/huggingface/datasets/issues/1827 | 802,353,974 | MDU6SXNzdWU4MDIzNTM5NzQ= | 1,827 | Regarding On-the-fly Data Loading | {
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"Possible duplicate\r\n\r\n#1776 https://github.com/huggingface/datasets/issues/\r\n\r\nreally looking PR for this feature",
"Hi @acul3 \r\n\r\nIssue #1776 talks about doing on-the-fly data pre-processing, which I think is solved in the next release as mentioned in the issue #1825. I also look forward to using t... | 1,612,547,028,000 | 1,613,656,516,000 | 1,613,656,516,000 | CONTRIBUTOR | null | Hi,
I was wondering if it is possible to load images/texts as a batch during the training process, without loading the entire dataset on the RAM at any given point.
Thanks,
Gunjan | {
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https://api.github.com/repos/huggingface/datasets/issues/1825 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1825/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1825/comments | https://api.github.com/repos/huggingface/datasets/issues/1825/events | https://github.com/huggingface/datasets/issues/1825 | 802,073,925 | MDU6SXNzdWU4MDIwNzM5MjU= | 1,825 | Datasets library not suitable for huge text datasets. | {
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"Hi ! Looks related to #861 \r\n\r\nYou are right: tokenizing a dataset using map takes a lot of space since it can store `input_ids` but also `token_type_ids`, `attention_mask` and `special_tokens_mask`. Moreover if your tokenization function returns python integers then by default they'll be stored as int64 which... | 1,612,523,210,000 | 1,617,113,041,000 | 1,615,887,840,000 | NONE | null | Hi,
I'm trying to use datasets library to load a 187GB dataset of pure text, with the intention of building a Language Model. The problem is that from the 187GB it goes to some TB when processed by Datasets. First of all, I think the pre-tokenizing step (with tokenizer.map()) is not really thought for datasets this ... | {
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https://api.github.com/repos/huggingface/datasets/issues/1821 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1821/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1821/comments | https://api.github.com/repos/huggingface/datasets/issues/1821/events | https://github.com/huggingface/datasets/issues/1821 | 801,747,647 | MDU6SXNzdWU4MDE3NDc2NDc= | 1,821 | Provide better exception message when one of many files results in an exception | {
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"Hi!\r\n\r\nThank you for reporting this issue. I agree that the information about the exception should be more clear and explicit.\r\n\r\nI could take on this issue.\r\n\r\nOn the meantime, as you can see from the exception stack trace, HF Datasets uses pandas to read the CSV files. You can pass arguments to `pand... | 1,612,486,143,000 | 1,612,892,367,000 | 1,612,892,367,000 | NONE | null | I find when I process many files, i.e.
```
train_files = glob.glob('rain*.csv')
validation_files = glob.glob(validation*.csv')
datasets = load_dataset("csv", data_files=dict(train=train_files, validation=validation_files))
```
I sometimes encounter an error due to one of the files being misformed (i.e. no dat... | {
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https://api.github.com/repos/huggingface/datasets/issues/1818 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1818/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1818/comments | https://api.github.com/repos/huggingface/datasets/issues/1818/events | https://github.com/huggingface/datasets/issues/1818 | 800,958,776 | MDU6SXNzdWU4MDA5NTg3NzY= | 1,818 | Loading local dataset raise requests.exceptions.ConnectTimeout | {
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"Hi ! Thanks for reporting. This was indeed a bug introduced when we moved the `json` dataset loader inside the `datasets` package (before that, the `json` loader was fetched online, as all the other dataset scripts).\r\n\r\nThis should be fixed on master now. Feel free to install `datasets` from source to try it o... | 1,612,418,123,000 | 1,612,531,415,000 | null | NONE | null | Load local dataset:
```
dataset = load_dataset('json', data_files=["../../data/json.json"])
train = dataset["train"]
print(train.features)
train1 = train.map(lambda x: {"labels": 1})
print(train1[:2])
```
but it raised requests.exceptions.ConnectTimeout:
```
/Users/littlely/myvirtual/tf2/bin/python3.7 /Us... | {
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https://api.github.com/repos/huggingface/datasets/issues/1817 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1817/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1817/comments | https://api.github.com/repos/huggingface/datasets/issues/1817/events | https://github.com/huggingface/datasets/issues/1817 | 800,870,652 | MDU6SXNzdWU4MDA4NzA2NTI= | 1,817 | pyarrow.lib.ArrowInvalid: Column 1 named input_ids expected length 599 but got length 1500 | {
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"Hi !\r\nThe error you have is due to the `input_ids` column not having the same number of examples as the other columns.\r\nIndeed you're concatenating the `input_ids` at this line:\r\n\r\nhttps://github.com/LuCeHe/GenericTools/blob/431835d8e13ec24dceb5ee4dc4ae58f0e873b091/KerasTools/lm_preprocessing.py#L134\r\n\r... | 1,612,405,823,000 | 1,612,706,664,000 | null | NONE | null | I am trying to preprocess any dataset in this package with GPT-2 tokenizer, so I need to structure the datasets as long sequences of text without padding. I've been following a couple of your tutorials and here you can find the script that is failing right at the end
https://github.com/LuCeHe/GenericTools/blob/maste... | {
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https://api.github.com/repos/huggingface/datasets/issues/1811 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1811/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1811/comments | https://api.github.com/repos/huggingface/datasets/issues/1811/events | https://github.com/huggingface/datasets/issues/1811 | 799,211,060 | MDU6SXNzdWU3OTkyMTEwNjA= | 1,811 | Unable to add Multi-label Datasets | {
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"Thanks for adding this dataset! As far as I know `supervised_keys` is mostly a holdover from TFDS, but isn't really used, so feel free to drop it (@lhoestq or @thomwolf correct me if I'm wrong). It definitely shouldn't be blocking :) ",
"I can confirm that it comes from TFDS and is not used at the moment.",
"... | 1,612,266,656,000 | 1,613,657,791,000 | 1,613,657,791,000 | CONTRIBUTOR | null | I am trying to add [CIFAR-100](https://www.cs.toronto.edu/~kriz/cifar.html) dataset. The dataset contains two labels per image - `fine label` and `coarse label`. Using just one label in supervised keys as
`supervised_keys=("img", "fine_label")` raises no issue. But trying `supervised_keys=("img", "fine_label","coarse... | {
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https://api.github.com/repos/huggingface/datasets/issues/1810 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1810/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1810/comments | https://api.github.com/repos/huggingface/datasets/issues/1810/events | https://github.com/huggingface/datasets/issues/1810 | 799,168,650 | MDU6SXNzdWU3OTkxNjg2NTA= | 1,810 | Add Hateful Memes Dataset | {
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"I am not sure, but would `datasets.Sequence(datasets.Sequence(datasets.Sequence(datasets.Value(\"int\")))` work?",
"Also, I found the information for loading only subsets of the data [here](https://github.com/huggingface/datasets/blob/master/docs/source/splits.rst).",
"Hi @lhoestq,\r\n\r\nRequest you to check ... | 1,612,263,239,000 | 1,638,965,039,000 | null | CONTRIBUTOR | null | ## Add Hateful Memes Dataset
- **Name:** Hateful Memes
- **Description:** [https://ai.facebook.com/blog/hateful-memes-challenge-and-data-set]( https://ai.facebook.com/blog/hateful-memes-challenge-and-data-set)
- **Paper:** [https://arxiv.org/pdf/2005.04790.pdf](https://arxiv.org/pdf/2005.04790.pdf)
- **Data:** [Thi... | {
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https://api.github.com/repos/huggingface/datasets/issues/1808 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1808/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1808/comments | https://api.github.com/repos/huggingface/datasets/issues/1808/events | https://github.com/huggingface/datasets/issues/1808 | 798,879,180 | MDU6SXNzdWU3OTg4NzkxODA= | 1,808 | writing Datasets in a human readable format | {
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"AFAIK, there is currently no built-in method on the `Dataset` object to do this.\r\nHowever, a workaround is to directly use the Arrow table backing the dataset, **but it implies loading the whole dataset in memory** (correct me if I'm mistaken @lhoestq).\r\n\r\nYou can convert the Arrow table to a pandas datafram... | 1,612,234,540,000 | 1,612,278,248,000 | null | NONE | null | Hi
I see there is a save_to_disk function to save data, but this is not human readable format, is there a way I could save a Dataset object in a human readable format to a file like json? thanks @lhoestq | {
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https://api.github.com/repos/huggingface/datasets/issues/1805 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1805/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1805/comments | https://api.github.com/repos/huggingface/datasets/issues/1805/events | https://github.com/huggingface/datasets/issues/1805 | 798,498,053 | MDU6SXNzdWU3OTg0OTgwNTM= | 1,805 | can't pickle SwigPyObject objects when calling dataset.get_nearest_examples from FAISS index | {
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"Hi ! Indeed we used to require mapping functions to be picklable with `pickle` or `dill` in order to cache the resulting datasets. And FAISS indexes are not picklable unfortunately.\r\n\r\nBut since #1703 this is no longer required (the caching will simply be disabled). This change will be available in the next re... | 1,612,196,057,000 | 1,615,041,166,000 | 1,615,041,166,000 | CONTRIBUTOR | null | So, I have the following instances in my dataset
```
{'question': 'An astronomer observes that a planet rotates faster after a meteorite impact. Which is the most likely effect of
this increase in rotation?',
'answer': 'C',
'example_id': 'ARCCH_Mercury_7175875',
'options':[{'option_context': 'One effect of ... | {
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https://api.github.com/repos/huggingface/datasets/issues/1803 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1803/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1803/comments | https://api.github.com/repos/huggingface/datasets/issues/1803/events | https://github.com/huggingface/datasets/issues/1803 | 798,243,904 | MDU6SXNzdWU3OTgyNDM5MDQ= | 1,803 | Querying examples from big datasets is slower than small datasets | {
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"Hello, @lhoestq / @gaceladri : We have been seeing similar behavior with bigger datasets, where querying time increases. Are you folks aware of any solution that fixes this problem yet? ",
"Hi ! I'm pretty sure that it can be fixed by using the Arrow IPC file format instead of the raw streaming format but I ha... | 1,612,177,703,000 | 1,628,100,661,000 | 1,628,100,642,000 | MEMBER | null | After some experiments with bookcorpus I noticed that querying examples from big datasets is slower than small datasets.
For example
```python
from datasets import load_dataset
b1 = load_dataset("bookcorpus", split="train[:1%]")
b50 = load_dataset("bookcorpus", split="train[:50%]")
b100 = load_dataset("bookcorp... | {
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https://api.github.com/repos/huggingface/datasets/issues/1797 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1797/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1797/comments | https://api.github.com/repos/huggingface/datasets/issues/1797/events | https://github.com/huggingface/datasets/issues/1797 | 797,357,901 | MDU6SXNzdWU3OTczNTc5MDE= | 1,797 | Connection error | {
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"Hi ! For future references let me add a link to our discussion here : https://github.com/huggingface/datasets/issues/759#issuecomment-770684693\r\n\r\nLet me know if you manage to fix your proxy issue or if we can do something on our end to help you :)"
] | 1,611,991,965,000 | 1,628,100,577,000 | 1,628,100,577,000 | NONE | null | Hi
I am hitting to the error, help me and thanks.
`train_data = datasets.load_dataset("xsum", split="train")`
`ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.0.2/datasets/xsum/xsum.py` | {
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https://api.github.com/repos/huggingface/datasets/issues/1796 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1796/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1796/comments | https://api.github.com/repos/huggingface/datasets/issues/1796/events | https://github.com/huggingface/datasets/issues/1796 | 797,329,905 | MDU6SXNzdWU3OTczMjk5MDU= | 1,796 | Filter on dataset too much slowww | {
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"When I use the filter on the arrow table directly, it works like butter. But I can't find a way to update the table in `Dataset` object.\r\n\r\n```\r\nds_table = dataset.data.filter(mask=dataset['flag'])\r\n```",
"@thomwolf @lhoestq can you guys please take a look and recommend some solution.",
"Hi ! Currently... | 1,611,979,759,000 | 1,613,668,164,000 | null | NONE | null | I have a dataset with 50M rows.
For pre-processing, I need to tokenize this and filter rows with the large sequence.
My tokenization took roughly 12mins. I used `map()` with batch size 1024 and multi-process with 96 processes.
When I applied the `filter()` function it is taking too much time. I need to filter se... | {
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https://api.github.com/repos/huggingface/datasets/issues/1790 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1790/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1790/comments | https://api.github.com/repos/huggingface/datasets/issues/1790/events | https://github.com/huggingface/datasets/issues/1790 | 796,678,157 | MDU6SXNzdWU3OTY2NzgxNTc= | 1,790 | ModuleNotFoundError: No module named 'apache_beam', when specific languages. | {
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"Hi !\r\n\r\nApache Beam is a framework used to define data transformation pipelines. These pipeline can then be run in many runtimes: DataFlow, Spark, Flink, etc. There also exist a local runner called the DirectRunner.\r\nWikipedia is a dataset that requires some parsing, so to allow the processing to be run on t... | 1,611,908,244,000 | 1,616,674,251,000 | null | CONTRIBUTOR | null | ```py
import datasets
wiki = datasets.load_dataset('wikipedia', '20200501.ja', cache_dir='./datasets')
```
then `ModuleNotFoundError: No module named 'apache_beam'` happend.
The error doesn't appear when it's '20200501.en'.
I don't know Apache Beam, but according to #498 it isn't necessary when it's saved to lo... | {
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https://api.github.com/repos/huggingface/datasets/issues/1786 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1786/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1786/comments | https://api.github.com/repos/huggingface/datasets/issues/1786/events | https://github.com/huggingface/datasets/issues/1786 | 795,462,816 | MDU6SXNzdWU3OTU0NjI4MTY= | 1,786 | How to use split dataset | {
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"By default, all 3 splits will be loaded if you run the following:\r\n\r\n```python\r\nfrom datasets import load_dataset\r\ndataset = load_dataset(\"lambada\")\r\nprint(dataset[\"train\"])\r\nprint(dataset[\"valid\"])\r\n\r\n```\r\n\r\nIf you wanted to do load this manually, you could do this:\r\n\r\n```python\r\nf... | 1,611,783,467,000 | 1,619,191,059,000 | 1,619,191,059,000 | NONE | null | 
Hey,
I want to split the lambada dataset into corpus, test, train and valid txt files (like penn treebank) but I am not able to achieve this. What I am doing is, executing the lambada.py file in my pro... | {
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https://api.github.com/repos/huggingface/datasets/issues/1785 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1785/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1785/comments | https://api.github.com/repos/huggingface/datasets/issues/1785/events | https://github.com/huggingface/datasets/issues/1785 | 795,458,856 | MDU6SXNzdWU3OTU0NTg4NTY= | 1,785 | Not enough disk space (Needed: Unknown size) when caching on a cluster | {
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"Hi ! \r\n\r\nWhat do you mean by \"disk_usage(\".\").free` can't compute on the cluster's shared disk\" exactly ?\r\nDoes it return 0 ?",
"Yes, that's right. It shows 0 free space even though there is. I suspect it might have to do with permissions on the shared disk.\r\n\r\n```python\r\n>>> disk_usage(\".\")\r\... | 1,611,783,059,000 | 1,611,968,876,000 | 1,611,968,876,000 | CONTRIBUTOR | null | I'm running some experiments where I'm caching datasets on a cluster and accessing it through multiple compute nodes. However, I get an error when loading the cached dataset from the shared disk.
The exact error thrown:
```bash
>>> load_dataset(dataset, cache_dir="/path/to/cluster/shared/path")
OSError: Not eno... | {
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https://api.github.com/repos/huggingface/datasets/issues/1784 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1784/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1784/comments | https://api.github.com/repos/huggingface/datasets/issues/1784/events | https://github.com/huggingface/datasets/issues/1784 | 794,659,174 | MDU6SXNzdWU3OTQ2NTkxNzQ= | 1,784 | JSONDecodeError on JSON with multiple lines | {
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"Hi !\r\n\r\nThe `json` dataset script does support this format. For example loading a dataset with this format works on my side:\r\n```json\r\n{\"key1\":11, \"key2\":12, \"key3\":13}\r\n{\"key1\":21, \"key2\":22, \"key3\":23}\r\n```\r\n\r\nCan you show the full stacktrace please ? Also which version of datasets an... | 1,611,706,762,000 | 1,612,082,838,000 | 1,612,082,838,000 | CONTRIBUTOR | null | Hello :),
I have been trying to load data using a JSON file. Based on the [docs](https://huggingface.co/docs/datasets/loading_datasets.html#json-files), the following format is supported:
```json
{"key1":11, "key2":12, "key3":13}
{"key1":21, "key2":22, "key3":23}
```
But, when I try loading a dataset with th... | {
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https://api.github.com/repos/huggingface/datasets/issues/1783 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1783/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1783/comments | https://api.github.com/repos/huggingface/datasets/issues/1783/events | https://github.com/huggingface/datasets/issues/1783 | 794,544,495 | MDU6SXNzdWU3OTQ1NDQ0OTU= | 1,783 | Dataset Examples Explorer | {
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"Hi @ChewKokWah,\r\n\r\nWe're working on it! In the meantime, you can still find the dataset explorer at the following URL: https://huggingface.co/datasets/viewer/",
"Glad to see that it still exist, this existing one is more than good enough for me, it is feature rich, simple to use and concise. \r\nHope similar... | 1,611,693,542,000 | 1,612,187,924,000 | 1,612,187,924,000 | NONE | null | In the Older version of the Dataset, there are a useful Dataset Explorer that allow user to visualize the examples (training, test and validation) of a particular dataset, it is no longer there in current version.
Hope HuggingFace can re-enable the feature that at least allow viewing of the first 20 examples of a ... | {
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https://api.github.com/repos/huggingface/datasets/issues/1781 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1781/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1781/comments | https://api.github.com/repos/huggingface/datasets/issues/1781/events | https://github.com/huggingface/datasets/issues/1781 | 793,914,556 | MDU6SXNzdWU3OTM5MTQ1NTY= | 1,781 | AttributeError: module 'pyarrow' has no attribute 'PyExtensionType' during import | {
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"Hi ! I'm not able to reproduce the issue. Can you try restarting your runtime ?\r\n\r\nThe PyExtensionType is available in pyarrow starting 0.17.1 iirc. If restarting your runtime doesn't fix this, can you try updating pyarrow ?\r\n```\r\npip install pyarrow --upgrade\r\n```",
"We should bump up the version test... | 1,611,634,715,000 | 1,611,661,656,000 | null | NONE | null | I'm using Colab. And suddenly this morning, there is this error. Have a look below!
| {
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https://api.github.com/repos/huggingface/datasets/issues/1777 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1777/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1777/comments | https://api.github.com/repos/huggingface/datasets/issues/1777/events | https://github.com/huggingface/datasets/issues/1777 | 793,273,770 | MDU6SXNzdWU3OTMyNzM3NzA= | 1,777 | GPT2 MNLI training using run_glue.py | {
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Running this on Google Colab,
```
!python run_glue.py \
--model_name_or_path gpt2 \
--task_name mnli \
--do_train \
--do_eval \
--max_seq_length 128 \
--per_gpu_train_batch_size 10 \
--gradient_accu... | {
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https://api.github.com/repos/huggingface/datasets/issues/1776 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1776/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1776/comments | https://api.github.com/repos/huggingface/datasets/issues/1776/events | https://github.com/huggingface/datasets/issues/1776 | 792,755,249 | MDU6SXNzdWU3OTI3NTUyNDk= | 1,776 | [Question & Bug Report] Can we preprocess a dataset on the fly? | {
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"We are very actively working on this. How does your dataset look like in practice (number/size/type of files)?",
"It's a text file with many lines (about 1B) of Chinese sentences. I use it to train language model using https://github.com/huggingface/transformers/blob/master/examples/language-modeling/run_mlm_wwm... | 1,611,480,504,000 | 1,621,484,158,000 | 1,621,484,158,000 | NONE | null | I know we can use `Datasets.map` to preprocess a dataset, but I'm using it with very large corpus which generates huge cache file (several TB cache from a 400 GB text file). I have no disk large enough to save it. Can we preprocess a dataset on the fly without generating cache?
BTW, I tried raising `writer_batch_si... | {
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https://api.github.com/repos/huggingface/datasets/issues/1775 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1775/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1775/comments | https://api.github.com/repos/huggingface/datasets/issues/1775/events | https://github.com/huggingface/datasets/issues/1775 | 792,742,120 | MDU6SXNzdWU3OTI3NDIxMjA= | 1,775 | Efficient ways to iterate the dataset | {
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"It seems that selecting a subset of colums directly from the dataset, i.e., dataset[\"column\"], is slow.",
"I was wrong, ```dataset[\"column\"]``` is fast."
] | 1,611,474,871,000 | 1,611,481,839,000 | 1,611,481,839,000 | CONTRIBUTOR | null | For a large dataset that does not fits the memory, how can I select only a subset of features from each example?
If I iterate over the dataset and then select the subset of features one by one, the resulted memory usage will be huge. Any ways to solve this?
Thanks | {
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https://api.github.com/repos/huggingface/datasets/issues/1774 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1774/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1774/comments | https://api.github.com/repos/huggingface/datasets/issues/1774/events | https://github.com/huggingface/datasets/issues/1774 | 792,730,559 | MDU6SXNzdWU3OTI3MzA1NTk= | 1,774 | is it possible to make slice to be more compatible like python list and numpy? | {
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"Hi ! Thanks for reporting.\r\nI am working on changes in the way data are sliced from arrow. I can probably fix your issue with the changes I'm doing.\r\nIf you have some code to reproduce the issue it would be nice so I can make sure that this case will be supported :)\r\nI'll make a PR in a few days ",
"Good i... | 1,611,468,952,000 | 1,611,531,378,000 | null | NONE | null | Hi,
see below error:
```
AssertionError: Requested slice [:10000000000000000] incompatible with 20 examples.
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/1773 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1773/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1773/comments | https://api.github.com/repos/huggingface/datasets/issues/1773/events | https://github.com/huggingface/datasets/issues/1773 | 792,708,160 | MDU6SXNzdWU3OTI3MDgxNjA= | 1,773 | bug in loading datasets | {
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"Looks like an issue with your csv file. Did you use the right delimiter ?\r\nApparently at line 37 the CSV reader from pandas reads 2 fields instead of 1.",
"Note that you can pass any argument you would pass to `pandas.read_csv` as kwargs to `load_dataset`. For example you can do\r\n```python\r\nfrom datasets i... | 1,611,456,825,000 | 1,630,918,486,000 | 1,628,100,781,000 | NONE | null | Hi,
I need to load a dataset, I use these commands:
```
from datasets import load_dataset
dataset = load_dataset('csv', data_files={'train': 'sick/train.csv',
'test': 'sick/test.csv',
'validation': 'sick/validation.csv'})
prin... | {
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https://api.github.com/repos/huggingface/datasets/issues/1772 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1772/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1772/comments | https://api.github.com/repos/huggingface/datasets/issues/1772/events | https://github.com/huggingface/datasets/issues/1772 | 792,703,797 | MDU6SXNzdWU3OTI3MDM3OTc= | 1,772 | Adding SICK dataset | {
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It would be great to include SICK dataset.
## Adding a Dataset
- **Name:** SICK
- **Description:** a well known entailment dataset
- **Paper:** http://marcobaroni.org/composes/sick.html
- **Data:** http://marcobaroni.org/composes/sick.html
- **Motivation:** this is an important NLI benchmark
Instruction... | {
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https://api.github.com/repos/huggingface/datasets/issues/1771 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1771/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1771/comments | https://api.github.com/repos/huggingface/datasets/issues/1771/events | https://github.com/huggingface/datasets/issues/1771 | 792,701,276 | MDU6SXNzdWU3OTI3MDEyNzY= | 1,771 | Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.2.1/datasets/csv/csv.py | {
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"I temporary manually download csv.py as custom dataset loading script",
"Indeed in 1.2.1 the script to process csv file is downloaded. Starting from the next release though we include the csv processing directly in the library.\r\nSee PR #1726 \r\nWe'll do a new release soon :)",
"Thanks."
] | 1,611,453,232,000 | 1,611,529,589,000 | 1,611,529,589,000 | NONE | null | Hi,
When I load_dataset from local csv files, below error happened, looks raw.githubusercontent.com was blocked by the chinese government. But why it need to download csv.py? should it include when pip install the dataset?
```
Traceback (most recent call last):
File "/home/tom/pyenv/pystory/lib/python3.6/site-p... | {
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https://api.github.com/repos/huggingface/datasets/issues/1770 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1770/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1770/comments | https://api.github.com/repos/huggingface/datasets/issues/1770/events | https://github.com/huggingface/datasets/issues/1770 | 792,698,148 | MDU6SXNzdWU3OTI2OTgxNDg= | 1,770 | how can I combine 2 dataset with different/same features? | {
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"Hi ! Currently we don't have a way to `zip` datasets but we plan to add this soon :)\r\nFor now you'll need to use `map` to add the fields from one dataset to the other. See the comment here for more info : https://github.com/huggingface/datasets/issues/853#issuecomment-727872188",
"Good to hear.\r\nCurrently I ... | 1,611,451,566,000 | 1,611,531,834,000 | null | NONE | null | to combine 2 dataset by one-one map like ds = zip(ds1, ds2):
ds1: {'text'}, ds2: {'text'}, combine ds:{'src', 'tgt'}
or different feature:
ds1: {'src'}, ds2: {'tgt'}, combine ds:{'src', 'tgt'} | {
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https://api.github.com/repos/huggingface/datasets/issues/1769 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1769/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1769/comments | https://api.github.com/repos/huggingface/datasets/issues/1769/events | https://github.com/huggingface/datasets/issues/1769 | 792,523,284 | MDU6SXNzdWU3OTI1MjMyODQ= | 1,769 | _pickle.PicklingError: Can't pickle typing.Union[str, NoneType]: it's not the same object as typing.Union when calling datasets.map with num_proc=2 | {
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"More information: `run_mlm.py` will raise same error when `data_args.line_by_line==True`\r\n\r\nhttps://github.com/huggingface/transformers/blob/9152f16023b59d262b51573714b40325c8e49370/examples/language-modeling/run_mlm.py#L300\r\n",
"Hi ! What version of python and datasets do you have ? And also what version ... | 1,611,396,780,000 | 1,611,570,237,000 | null | NONE | null | It may be a bug of multiprocessing with Datasets, when I disable the multiprocessing by set num_proc to None, everything works fine.
The script I use is https://github.com/huggingface/transformers/blob/master/examples/language-modeling/run_mlm_wwm.py
Script args:
```
--model_name_or_path
../../../model/chine... | {
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https://api.github.com/repos/huggingface/datasets/issues/1766 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1766/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1766/comments | https://api.github.com/repos/huggingface/datasets/issues/1766/events | https://github.com/huggingface/datasets/issues/1766 | 792,044,105 | MDU6SXNzdWU3OTIwNDQxMDU= | 1,766 | Issues when run two programs compute the same metrics | {
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"Hi ! To avoid collisions you can specify a `experiment_id` when instantiating your metric using `load_metric`. It will replace \"default_experiment\" with the experiment id that you provide in the arrow filename. \r\n\r\nAlso when two `experiment_id` collide we're supposed to detect it using our locking mechanism.... | 1,611,325,375,000 | 1,612,262,286,000 | 1,612,262,286,000 | NONE | null | I got the following error when running two different programs that both compute sacreblue metrics. It seems that both read/and/write to the same location (.cache/huggingface/metrics/sacrebleu/default/default_experiment-1-0.arrow) where it caches the batches:
```
File "train_matching_min.py", line 160, in <module>ch... | {
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https://api.github.com/repos/huggingface/datasets/issues/1765 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1765/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1765/comments | https://api.github.com/repos/huggingface/datasets/issues/1765/events | https://github.com/huggingface/datasets/issues/1765 | 791,553,065 | MDU6SXNzdWU3OTE1NTMwNjU= | 1,765 | Error iterating over Dataset with DataLoader | {
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"Instead of:\r\n```python\r\ndataloader = torch.utils.data.DataLoader(encoded_dataset, batch_sampler=32)\r\n```\r\nIt should be:\r\n```python\r\ndataloader = torch.utils.data.DataLoader(encoded_dataset, batch_size=32)\r\n```\r\n\r\n`batch_sampler` accepts a Sampler object or an Iterable, so you get an error.",
"@... | 1,611,269,805,000 | 1,638,879,753,000 | 1,611,373,454,000 | NONE | null | I have a Dataset that I've mapped a tokenizer over:
```
encoded_dataset.set_format(type='torch',columns=['attention_mask','input_ids','token_type_ids'])
encoded_dataset[:1]
```
```
{'attention_mask': tensor([[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]),
'input_ids': tensor([[ 101, 178, 1198, 1400, 1714, 22233, 2... | {
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https://api.github.com/repos/huggingface/datasets/issues/1764 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1764/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1764/comments | https://api.github.com/repos/huggingface/datasets/issues/1764/events | https://github.com/huggingface/datasets/issues/1764 | 791,486,860 | MDU6SXNzdWU3OTE0ODY4NjA= | 1,764 | Connection Issues | {
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"Academic WIFI was blocking."
] | 1,611,262,569,000 | 1,611,262,819,000 | 1,611,262,802,000 | NONE | null | Today, I am getting connection issues while loading a dataset and the metric.
```
Traceback (most recent call last):
File "src/train.py", line 180, in <module>
train_dataset, dev_dataset, test_dataset = create_race_dataset()
File "src/train.py", line 130, in create_race_dataset
train_dataset = load_da... | {
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https://api.github.com/repos/huggingface/datasets/issues/1762 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1762/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1762/comments | https://api.github.com/repos/huggingface/datasets/issues/1762/events | https://github.com/huggingface/datasets/issues/1762 | 791,226,007 | MDU6SXNzdWU3OTEyMjYwMDc= | 1,762 | Unable to format dataset to CUDA Tensors | {
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"Hi ! You can get CUDA tensors with\r\n\r\n```python\r\ndataset.set_format(\"torch\", columns=columns, device=\"cuda\")\r\n```\r\n\r\nIndeed `set_format` passes the `**kwargs` to `torch.tensor`",
"Hi @lhoestq,\r\n\r\nThanks a lot. Is this true for all format types?\r\n\r\nAs in, for 'torch', I can have `**kwargs`... | 1,611,243,083,000 | 1,612,250,002,000 | 1,612,250,002,000 | CONTRIBUTOR | null | Hi,
I came across this [link](https://huggingface.co/docs/datasets/torch_tensorflow.html) where the docs show show to convert a dataset to a particular format. I see that there is an option to convert it to tensors, but I don't see any option to convert it to CUDA tensors.
I tried this, but Dataset doesn't suppor... | {
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https://api.github.com/repos/huggingface/datasets/issues/1759 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1759/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1759/comments | https://api.github.com/repos/huggingface/datasets/issues/1759/events | https://github.com/huggingface/datasets/issues/1759 | 790,992,226 | MDU6SXNzdWU3OTA5OTIyMjY= | 1,759 | wikipedia dataset incomplete | {
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"Hi !\r\nFrom what pickle file fo you get this ?\r\nI guess you mean the dataset loaded using `load_dataset` ?",
"yes sorry, I used the `load_dataset`function and saved the data to a pickle file so I don't always have to reload it and are able to work offline. ",
"The wikipedia articles are processed using the ... | 1,611,229,635,000 | 1,611,249,731,000 | 1,611,249,666,000 | NONE | null | Hey guys,
I am using the https://github.com/huggingface/datasets/tree/master/datasets/wikipedia dataset.
Unfortunately, I found out that there is an incompleteness for the German dataset.
For reasons unknown to me, the number of inhabitants has been removed from many pages:
Thorey-sur-Ouche has 128 inhabitants a... | {
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https://api.github.com/repos/huggingface/datasets/issues/1758 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1758/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1758/comments | https://api.github.com/repos/huggingface/datasets/issues/1758/events | https://github.com/huggingface/datasets/issues/1758 | 790,626,116 | MDU6SXNzdWU3OTA2MjYxMTY= | 1,758 | dataset.search() (elastic) cannot reliably retrieve search results | {
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"Hi !\r\nI tried your code on my side and I was able to workaround this issue by waiting a few seconds before querying the index.\r\nMaybe this is because the index is not updated yet on the ElasticSearch side ?",
"Thanks for the feedback! I added a 30 second \"sleep\" and that seemed to work well!"
] | 1,611,195,997,000 | 1,611,275,150,000 | 1,611,275,150,000 | NONE | null | I am trying to use elastic search to retrieve the indices of items in the dataset in their precise order, given shuffled training indices.
The problem I have is that I cannot retrieve reliable results with my data on my first search. I have to run the search **twice** to get the right answer.
I am indexing data t... | {
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https://api.github.com/repos/huggingface/datasets/issues/1757 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1757/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1757/comments | https://api.github.com/repos/huggingface/datasets/issues/1757/events | https://github.com/huggingface/datasets/issues/1757 | 790,466,509 | MDU6SXNzdWU3OTA0NjY1MDk= | 1,757 | FewRel | {
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"+1",
"@dspoka Please check the following link : https://github.com/thunlp/FewRel\r\nThis link mentions two versions of the datasets. Also, this one seems to be the official link.\r\n\r\nI am assuming this is the correct link and implementing based on the same.",
"Hi @lhoestq,\r\n\r\nThis issue can be closed, I... | 1,611,186,963,000 | 1,615,258,325,000 | 1,615,214,092,000 | NONE | null | ## Adding a Dataset
- **Name:** FewRel
- **Description:** Large-Scale Supervised Few-Shot Relation Classification Dataset
- **Paper:** @inproceedings{han2018fewrel,
title={FewRel:A Large-Scale Supervised Few-Shot Relation Classification Dataset with State-of-the-Art Evaluation},
auth... | {
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https://api.github.com/repos/huggingface/datasets/issues/1756 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1756/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1756/comments | https://api.github.com/repos/huggingface/datasets/issues/1756/events | https://github.com/huggingface/datasets/issues/1756 | 790,380,028 | MDU6SXNzdWU3OTAzODAwMjg= | 1,756 | Ccaligned multilingual translation dataset | {
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- **Name:** *name of the dataset*
- **Description:** *short description of the dataset (or link to social media or blog post)*
- CCAligned consists of parallel or comparable web-document pairs in 137 languages aligned with English. These web-document pairs were constructed by performing language ... | {
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https://api.github.com/repos/huggingface/datasets/issues/1755 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1755/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1755/comments | https://api.github.com/repos/huggingface/datasets/issues/1755/events | https://github.com/huggingface/datasets/issues/1755 | 790,324,734 | MDU6SXNzdWU3OTAzMjQ3MzQ= | 1,755 | Using select/reordering datasets slows operations down immensely | {
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"You can use `Dataset.flatten_indices()` to make it fast after a select or shuffle.",
"Thanks for the input! I gave that a try by adding this after my selection / reordering operations, but before the big computation task of `score_squad`\r\n\r\n```\r\nexamples = examples.flatten_indices()\r\nfeatures = features.... | 1,611,177,132,000 | 1,611,180,219,000 | 1,611,180,219,000 | NONE | null | I am using portions of HF's helpful work in preparing / scoring the SQuAD 2.0 data. The problem I have is that after using `select` to re-ordering the dataset, computations slow down immensely where the total scoring process on 131k training examples would take maybe 3 minutes, now take over an hour.
The below examp... | {
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https://api.github.com/repos/huggingface/datasets/issues/1747 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1747/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1747/comments | https://api.github.com/repos/huggingface/datasets/issues/1747/events | https://github.com/huggingface/datasets/issues/1747 | 788,299,775 | MDU6SXNzdWU3ODgyOTk3NzU= | 1,747 | datasets slicing with seed | {
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"Hi :) \r\nThe slicing API from https://huggingface.co/docs/datasets/splits.html doesn't shuffle the data.\r\nYou can shuffle and then take a subset of your dataset with\r\n```python\r\n# shuffle and take the first 100 examples\r\ndataset = dataset.shuffle(seed=42).select(range(100))\r\n```\r\n\r\nYou can find more... | 1,610,978,935,000 | 1,610,981,134,000 | null | NONE | null | Hi
I need to slice a dataset with random seed, I looked into documentation here https://huggingface.co/docs/datasets/splits.html
I could not find a seed option, could you assist me please how I can get a slice for different seeds?
thank you.
@lhoestq | {
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https://api.github.com/repos/huggingface/datasets/issues/1745 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1745/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1745/comments | https://api.github.com/repos/huggingface/datasets/issues/1745/events | https://github.com/huggingface/datasets/issues/1745 | 787,838,256 | MDU6SXNzdWU3ODc4MzgyNTY= | 1,745 | difference between wsc and wsc.fixed for superglue | {
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"From the description given in the dataset script for `wsc.fixed`:\r\n```\r\nThis version fixes issues where the spans are not actually substrings of the text.\r\n```"
] | 1,610,931,019,000 | 1,610,967,763,000 | 1,610,931,574,000 | NONE | null | Hi
I see two versions of wsc in superglue, and I am not sure what is the differences and which one is the original one. could you help to discuss the differences? thanks @lhoestq | {
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https://api.github.com/repos/huggingface/datasets/issues/1743 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1743/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1743/comments | https://api.github.com/repos/huggingface/datasets/issues/1743/events | https://github.com/huggingface/datasets/issues/1743 | 787,631,412 | MDU6SXNzdWU3ODc2MzE0MTI= | 1,743 | Issue while Creating Custom Metric | {
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"Currently it's only possible to define the features for the two columns `references` and `predictions`.\r\nThe data for these columns can then be passed to `metric.add_batch` and `metric.compute`.\r\nInstead of defining more columns `text`, `offset_mapping` and `ground` you must include them in either references a... | 1,610,866,874,000 | 1,611,333,900,000 | null | CONTRIBUTOR | null | Hi Team,
I am trying to create a custom metric for my training as follows, where f1 is my own metric:
```python
def _info(self):
# TODO: Specifies the datasets.MetricInfo object
return datasets.MetricInfo(
# This is the description that will appear on the metrics page.
... | {
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https://api.github.com/repos/huggingface/datasets/issues/1741 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1741/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1741/comments | https://api.github.com/repos/huggingface/datasets/issues/1741/events | https://github.com/huggingface/datasets/issues/1741 | 787,327,060 | MDU6SXNzdWU3ODczMjcwNjA= | 1,741 | error when run fine_tuning on text_classification | {
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"none"
] | 1,610,763,799,000 | 1,610,764,768,000 | 1,610,764,758,000 | NONE | null | dataset:sem_eval_2014_task_1
pretrained_model:bert-base-uncased
error description:
when i use these resoruce to train fine_tuning a text_classification on sem_eval_2014_task_1,there always be some problem(when i use other dataset ,there exist the error too). And i followed the colab code (url:https://colab.researc... | {
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https://api.github.com/repos/huggingface/datasets/issues/1733 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1733/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1733/comments | https://api.github.com/repos/huggingface/datasets/issues/1733/events | https://github.com/huggingface/datasets/issues/1733 | 784,903,002 | MDU6SXNzdWU3ODQ5MDMwMDI= | 1,733 | connection issue with glue, what is the data url for glue? | {
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"Hello @juliahane, which config of GLUE causes you trouble?\r\nThe URLs are defined in the dataset script source code: https://github.com/huggingface/datasets/blob/master/datasets/glue/glue.py"
] | 1,610,527,060,000 | 1,628,100,835,000 | 1,628,100,835,000 | NONE | null | Hi
my codes sometimes fails due to connection issue with glue, could you tell me how I can have the URL datasets library is trying to read GLUE from to test the machines I am working on if there is an issue on my side or not
thanks | {
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https://api.github.com/repos/huggingface/datasets/issues/1731 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1731/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1731/comments | https://api.github.com/repos/huggingface/datasets/issues/1731/events | https://github.com/huggingface/datasets/issues/1731 | 784,744,674 | MDU6SXNzdWU3ODQ3NDQ2NzQ= | 1,731 | Couldn't reach swda.py | {
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"Hi @yangp725,\r\nThe SWDA has been added very recently and has not been released yet, thus it is not available in the `1.2.0` version of 🤗`datasets`.\r\nYou can still access it by installing the latest version of the library (master branch), by following instructions in [this issue](https://github.com/huggingface... | 1,610,506,660,000 | 1,610,536,660,000 | 1,610,536,660,000 | NONE | null | ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.2.0/datasets/swda/swda.py
| {
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https://api.github.com/repos/huggingface/datasets/issues/1729 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1729/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1729/comments | https://api.github.com/repos/huggingface/datasets/issues/1729/events | https://github.com/huggingface/datasets/issues/1729 | 784,565,898 | MDU6SXNzdWU3ODQ1NjU4OTg= | 1,729 | Is there support for Deep learning datasets? | {
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"Hi @ZurMaD!\r\nThanks for your interest in 🤗 `datasets`. Support for image datasets is at an early stage, with CIFAR-10 added in #1617 \r\nMNIST is also on the way: #1730 \r\n\r\nIf you feel like adding another image dataset, I would advise starting by reading the [ADD_NEW_DATASET.md](https://github.com/huggingfa... | 1,610,482,961,000 | 1,617,164,647,000 | 1,617,164,647,000 | NONE | null | I looked around this repository and looking the datasets I think that there's no support for images-datasets. Or am I missing something? For example to add a repo like this https://github.com/DZPeru/fish-datasets | {
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https://api.github.com/repos/huggingface/datasets/issues/1728 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1728/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1728/comments | https://api.github.com/repos/huggingface/datasets/issues/1728/events | https://github.com/huggingface/datasets/issues/1728 | 784,458,342 | MDU6SXNzdWU3ODQ0NTgzNDI= | 1,728 | Add an entry to an arrow dataset | {
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"Hi @ameet-1997,\r\nI think what you are looking for is the `concatenate_datasets` function: https://huggingface.co/docs/datasets/processing.html?highlight=concatenate#concatenate-several-datasets\r\n\r\nFor your use case, I would use the [`map` method](https://huggingface.co/docs/datasets/processing.html?highlight... | 1,610,474,507,000 | 1,610,997,332,000 | 1,610,997,332,000 | NONE | null | Is it possible to add an entry to a dataset object?
**Motivation: I want to transform the sentences in the dataset and add them to the original dataset**
For example, say we have the following code:
``` python
from datasets import load_dataset
# Load a dataset and print the first examples in the training s... | {
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https://api.github.com/repos/huggingface/datasets/issues/1727 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1727/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1727/comments | https://api.github.com/repos/huggingface/datasets/issues/1727/events | https://github.com/huggingface/datasets/issues/1727 | 784,435,131 | MDU6SXNzdWU3ODQ0MzUxMzE= | 1,727 | BLEURT score calculation raises UnrecognizedFlagError | {
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"Upgrading tensorflow to version 2.4.0 solved the issue.",
"I still have the same error even with TF 2.4.0.",
"And I have the same error with TF 2.4.1. I believe this issue should be reopened. Any ideas?!",
"I'm seeing the same issue with TF 2.4.1 when running the following in https://colab.research.google.co... | 1,610,472,422,000 | 1,618,266,101,000 | null | NONE | null | Calling the `compute` method for **bleurt** metric fails with an `UnrecognizedFlagError` for `FLAGS.bleurt_batch_size`.
My environment:
```
python==3.8.5
datasets==1.2.0
tensorflow==2.3.1
cudatoolkit==11.0.221
```
Test code for reproducing the error:
```
from datasets import load_metric
bleurt = load_me... | {
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https://api.github.com/repos/huggingface/datasets/issues/1725 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1725/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1725/comments | https://api.github.com/repos/huggingface/datasets/issues/1725/events | https://github.com/huggingface/datasets/issues/1725 | 784,182,273 | MDU6SXNzdWU3ODQxODIyNzM= | 1,725 | load the local dataset | {
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"You should rephrase your question or give more examples and details on what you want to do.\r\n\r\nit’s not possible to understand it and help you with only this information.",
"sorry for that.\r\ni want to know how could i load the train set and the test set from the local ,which api or function should i use .\... | 1,610,453,575,000 | 1,614,768,943,000 | null | NONE | null | your guidebook's example is like
>>>from datasets import load_dataset
>>> dataset = load_dataset('json', data_files='my_file.json')
but the first arg is path...
so how should i do if i want to load the local dataset for model training?
i will be grateful if you can help me handle this problem!
thanks a lot! | {
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https://api.github.com/repos/huggingface/datasets/issues/1724 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1724/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1724/comments | https://api.github.com/repos/huggingface/datasets/issues/1724/events | https://github.com/huggingface/datasets/issues/1724 | 784,023,338 | MDU6SXNzdWU3ODQwMjMzMzg= | 1,724 | could not run models on a offline server successfully | {
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"Transferred to `datasets` based on the stack trace.",
"Hi @lkcao !\r\nYour issue is indeed related to `datasets`. In addition to installing the package manually, you will need to download the `text.py` script on your server. You'll find it (under `datasets/datasets/text`: https://github.com/huggingface/datasets/... | 1,610,431,686,000 | 1,614,785,549,000 | null | NONE | null | Hi, I really need your help about this.
I am trying to fine-tuning a RoBERTa on a remote server, which is strictly banning internet. I try to install all the packages by hand and try to run run_mlm.py on the server. It works well on colab, but when I try to run it on this offline server, it shows:
![image](https://us... | {
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https://api.github.com/repos/huggingface/datasets/issues/1718 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1718/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1718/comments | https://api.github.com/repos/huggingface/datasets/issues/1718/events | https://github.com/huggingface/datasets/issues/1718 | 783,474,753 | MDU6SXNzdWU3ODM0NzQ3NTM= | 1,718 | Possible cache miss in datasets | {
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"Thanks for reporting !\r\nI was able to reproduce thanks to your code and find the origin of the bug.\r\nThe cache was not reusing the same file because one object was not deterministic. It comes from a conversion from `set` to `list` in the `datasets.arrrow_dataset.transmit_format` function, where the resulting l... | 1,610,379,451,000 | 1,619,591,723,000 | 1,611,629,279,000 | NONE | null | Hi,
I am using the datasets package and even though I run the same data processing functions, datasets always recomputes the function instead of using cache.
I have attached an example script that for me reproduces the problem.
In the attached example the second map function always recomputes instead of loading fr... | {
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https://api.github.com/repos/huggingface/datasets/issues/1717 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1717/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1717/comments | https://api.github.com/repos/huggingface/datasets/issues/1717/events | https://github.com/huggingface/datasets/issues/1717 | 783,074,255 | MDU6SXNzdWU3ODMwNzQyNTU= | 1,717 | SciFact dataset - minor changes | {
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"Hi Dave,\r\nYou are more than welcome to open a PR to make these changes! 🤗\r\nYou will find the relevant information about opening a PR in the [contributing guide](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md) and in the [dataset addition guide](https://github.com/huggingface/datasets/blob... | 1,610,342,800,000 | 1,611,629,537,000 | 1,611,629,537,000 | CONTRIBUTOR | null | Hi,
SciFact dataset creator here. First of all, thanks for adding the dataset to Huggingface, much appreciated!
I'd like to make a few minor changes, including the citation information and the `_URL` from which to download the dataset. Can I submit a PR for this?
It also looks like the dataset is being downloa... | {
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https://api.github.com/repos/huggingface/datasets/issues/1713 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1713/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1713/comments | https://api.github.com/repos/huggingface/datasets/issues/1713/events | https://github.com/huggingface/datasets/issues/1713 | 782,337,723 | MDU6SXNzdWU3ODIzMzc3MjM= | 1,713 | Installation using conda | {
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"Yes indeed the idea is to have the next release on conda cc @LysandreJik ",
"Great! Did you guys have a timeframe in mind for the next release?\r\n\r\nThank you for all the great work in developing this library.",
"I think we can have `datasets` on conda by next week. Will see what I can do!",
"Thank you. Lo... | 1,610,133,135,000 | 1,631,882,860,000 | 1,631,882,860,000 | NONE | null | Will a conda package for installing datasets be added to the huggingface conda channel? I have installed transformers using conda and would like to use the datasets library to use some of the scripts in the transformers/examples folder but am unable to do so at the moment as datasets can only be installed using pip and... | {
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https://api.github.com/repos/huggingface/datasets/issues/1710 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1710/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1710/comments | https://api.github.com/repos/huggingface/datasets/issues/1710/events | https://github.com/huggingface/datasets/issues/1710 | 781,914,951 | MDU6SXNzdWU3ODE5MTQ5NTE= | 1,710 | IsADirectoryError when trying to download C4 | {
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"I haven't tested C4 on my side so there so there may be a few bugs in the code/adjustments to make.\r\nHere it looks like in c4.py, line 190 one of the `files_to_download` is `'/'` which is invalid.\r\nValid files are paths to local files or URLs to remote files."
] | 1,610,091,090,000 | 1,610,531,053,000 | null | NONE | null | **TLDR**:
I fail to download C4 and see a stacktrace originating in `IsADirectoryError` as an explanation for failure.
How can the problem be fixed?
**VERBOSE**:
I use Python version 3.7 and have the following dependencies listed in my project:
```
datasets==1.2.0
apache-beam==2.26.0
```
When runn... | {
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https://api.github.com/repos/huggingface/datasets/issues/1709 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1709/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1709/comments | https://api.github.com/repos/huggingface/datasets/issues/1709/events | https://github.com/huggingface/datasets/issues/1709 | 781,875,640 | MDU6SXNzdWU3ODE4NzU2NDA= | 1,709 | Databases | {
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- **Name:** *name of the dataset*
- **Description:** *short description of the dataset (or link to social media or blog post)*
- **Paper:** *link to the dataset paper if available*
- **Data:** *link to the Github repository or current dataset location*
- **Motivation:** *what are some good reasons t... | {
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https://api.github.com/repos/huggingface/datasets/issues/1708 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1708/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1708/comments | https://api.github.com/repos/huggingface/datasets/issues/1708/events | https://github.com/huggingface/datasets/issues/1708 | 781,631,455 | MDU6SXNzdWU3ODE2MzE0NTU= | 1,708 | <html dir="ltr" lang="en" class="focus-outline-visible"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"> | {
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- **Name:** *name of the dataset*
- **Description:** *short description of the dataset (or link to social media or blog post)*
- **Paper:** *link to the dataset paper if available*
- **Data:** *link to the Github repository or current dataset location*
- **Motivation:** *what are some good reasons t... | {
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https://api.github.com/repos/huggingface/datasets/issues/1706 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1706/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1706/comments | https://api.github.com/repos/huggingface/datasets/issues/1706/events | https://github.com/huggingface/datasets/issues/1706 | 781,494,476 | MDU6SXNzdWU3ODE0OTQ0NzY= | 1,706 | Error when downloading a large dataset on slow connection. | {
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"Hi ! Is this an issue you have with `openwebtext` specifically or also with other datasets ?\r\n\r\nIt looks like the downloaded file is corrupted and can't be extracted using `tarfile`.\r\nCould you try loading it again with \r\n```python\r\nimport datasets\r\ndatasets.load_dataset(\"openwebtext\", download_mode=... | 1,610,041,695,000 | 1,610,534,102,000 | null | CONTRIBUTOR | null | I receive the following error after about an hour trying to download the `openwebtext` dataset.
The code used is:
```python
import datasets
datasets.load_dataset("openwebtext")
```
> Traceback (most recent call last): ... | {
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https://api.github.com/repos/huggingface/datasets/issues/1701 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1701/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1701/comments | https://api.github.com/repos/huggingface/datasets/issues/1701/events | https://github.com/huggingface/datasets/issues/1701 | 781,345,717 | MDU6SXNzdWU3ODEzNDU3MTc= | 1,701 | Some datasets miss dataset_infos.json or dummy_data.zip | {
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"Thanks for reporting.\r\nWe should indeed add all the missing dummy_data.zip and also the dataset_infos.json at least for lm1b, reclor and wikihow.\r\n\r\nFor c4 I haven't tested the script and I think we'll require some optimizations regarding beam datasets before processing it.\r\n"
] | 1,610,029,033,000 | 1,610,458,846,000 | null | MEMBER | null | While working on dataset REAME generation script at https://github.com/madlag/datasets_readme_generator , I noticed that some datasets miss a dataset_infos.json :
```
c4
lm1b
reclor
wikihow
```
And some does not have a dummy_data.zip :
```
kor_nli
math_dataset
mlqa
ms_marco
newsgroup
qa4mre
qanga... | {
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https://api.github.com/repos/huggingface/datasets/issues/1696 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1696/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1696/comments | https://api.github.com/repos/huggingface/datasets/issues/1696/events | https://github.com/huggingface/datasets/issues/1696 | 781,096,918 | MDU6SXNzdWU3ODEwOTY5MTg= | 1,696 | Unable to install datasets | {
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"Maybe try to create a virtual env with python 3.8 or 3.7",
"Thanks, @thomwolf! I fixed the issue by downgrading python to 3.7. ",
"Damn sorry",
"Damn sorry"
] | 1,610,004,277,000 | 1,610,065,985,000 | 1,610,057,165,000 | NONE | null | ** Edit **
I believe there's a bug with the package when you're installing it with Python 3.9. I recommend sticking with previous versions. Thanks, @thomwolf for the insight!
**Short description**
I followed the instructions for installing datasets (https://huggingface.co/docs/datasets/installation.html). Howev... | {
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https://api.github.com/repos/huggingface/datasets/issues/1687 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1687/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1687/comments | https://api.github.com/repos/huggingface/datasets/issues/1687/events | https://github.com/huggingface/datasets/issues/1687 | 779,004,894 | MDU6SXNzdWU3NzkwMDQ4OTQ= | 1,687 | Question: Shouldn't .info be a part of DatasetDict? | {
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"We could do something. There is a part of `.info` which is split specific (cache files, split instructions) but maybe if could be made to work.",
"Yes this was kinda the idea I was going for. DatasetDict.info would be the shared info amongs the datasets (maybe even some info on how they differ). "
] | 1,609,852,121,000 | 1,610,014,686,000 | null | CONTRIBUTOR | null | Currently, only `Dataset` contains the .info or .features, but as many datasets contains standard splits (train, test) and thus the underlying information is the same (or at least should be) across the datasets.
For instance:
```
>>> ds = datasets.load_dataset("conll2002", "es")
>>> ds.info
Traceback (most rece... | {
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https://api.github.com/repos/huggingface/datasets/issues/1686 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1686/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1686/comments | https://api.github.com/repos/huggingface/datasets/issues/1686/events | https://github.com/huggingface/datasets/issues/1686 | 778,921,684 | MDU6SXNzdWU3Nzg5MjE2ODQ= | 1,686 | Dataset Error: DaNE contains empty samples at the end | {
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"Thanks for reporting, I opened a PR to fix that",
"One the PR is merged the fix will be available in the next release of `datasets`.\r\n\r\nIf you don't want to wait the next release you can still load the script from the master branch with\r\n\r\n```python\r\nload_dataset(\"dane\", script_version=\"master\")\r\... | 1,609,847,666,000 | 1,609,855,269,000 | 1,609,855,213,000 | CONTRIBUTOR | null | The dataset DaNE, contains empty samples at the end. It is naturally easy to remove using a filter but should probably not be there, to begin with as it can cause errors.
```python
>>> import datasets
[...]
>>> dataset = datasets.load_dataset("dane")
[...]
>>> dataset["test"][-1]
{'dep_ids': [], 'dep_labels': ... | {
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https://api.github.com/repos/huggingface/datasets/issues/1683 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1683/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1683/comments | https://api.github.com/repos/huggingface/datasets/issues/1683/events | https://github.com/huggingface/datasets/issues/1683 | 778,287,612 | MDU6SXNzdWU3NzgyODc2MTI= | 1,683 | `ArrowInvalid` occurs while running `Dataset.map()` function for DPRContext | {
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"Looks like the mapping function returns a dictionary with a 768-dim array in the `embeddings` field. Since the map is batched, we actually expect the `embeddings` field to be an array of shape (batch_size, 768) to have one embedding per example in the batch.\r\n\r\nTo fix that can you try to remove one of the `[0]... | 1,609,786,073,000 | 1,609,787,085,000 | 1,609,787,085,000 | CONTRIBUTOR | null | It seems to fail the final batch ):
steps to reproduce:
```
from datasets import load_dataset
from elasticsearch import Elasticsearch
import torch
from transformers import file_utils, set_seed
from transformers import DPRContextEncoder, DPRContextEncoderTokenizerFast
MAX_SEQ_LENGTH = 256
ctx_encoder = DPRCon... | {
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"Hi @KennethEnevoldsen ,\r\nI think the issue might be that this dataset was added during the community sprint and has not been released yet. It will be available with the v2 of datasets.\r\nFor now, you should be able to load the datasets after installing the latest (master) version of datasets using pip:\r\npip i... | 1,609,682,583,000 | 1,609,835,735,000 | 1,609,835,713,000 | CONTRIBUTOR | null | the `dane` dataset appear to be missing in the latest version (1.1.3).
```python
>>> import datasets
>>> datasets.__version__
'1.1.3'
>>> "dane" in datasets.list_datasets()
True
```
As we can see it should be present, but doesn't seem to be findable when using `load_dataset`.
```python
>>> datasets.load... | {
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https://api.github.com/repos/huggingface/datasets/issues/1679 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1679/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1679/comments | https://api.github.com/repos/huggingface/datasets/issues/1679/events | https://github.com/huggingface/datasets/issues/1679 | 777,587,792 | MDU6SXNzdWU3Nzc1ODc3OTI= | 1,679 | Can't import cc100 dataset | {
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"cc100 was added recently, that's why it wasn't available yet.\r\n\r\nTo load it you can just update `datasets`\r\n```\r\npip install --upgrade datasets\r\n```\r\n\r\nand then you can load `cc100` with\r\n\r\n```python\r\nfrom datasets import load_dataset\r\n\r\nlang = \"en\"\r\ndataset = load_dataset(\"cc100\", la... | 1,609,657,976,000 | 1,609,785,698,000 | null | NONE | null | There is some issue to import cc100 dataset.
```
from datasets import load_dataset
dataset = load_dataset("cc100")
```
FileNotFoundError: Couldn't find file at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/cc100/cc100.py
During handling of the above exception, another exception occur... | {
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https://api.github.com/repos/huggingface/datasets/issues/1675 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1675/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1675/comments | https://api.github.com/repos/huggingface/datasets/issues/1675/events | https://github.com/huggingface/datasets/issues/1675 | 777,367,320 | MDU6SXNzdWU3NzczNjczMjA= | 1,675 | Add the 800GB Pile dataset? | {
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"The pile dataset would be very nice.\r\nBenchmarks show that pile trained models achieve better results than most of actually trained models",
"The pile can very easily be added and adapted using this [tfds implementation](https://github.com/EleutherAI/The-Pile/blob/master/the_pile/tfds_pile.py) from the repo. \... | 1,609,541,892,000 | 1,638,372,547,000 | 1,638,372,547,000 | MEMBER | null | ## Adding a Dataset
- **Name:** The Pile
- **Description:** The Pile is a 825 GiB diverse, open source language modelling data set that consists of 22 smaller, high-quality datasets combined together. See [here](https://twitter.com/nabla_theta/status/1345130408170541056?s=20) for the Twitter announcement
- **Paper:*... | {
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https://api.github.com/repos/huggingface/datasets/issues/1674 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1674/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1674/comments | https://api.github.com/repos/huggingface/datasets/issues/1674/events | https://github.com/huggingface/datasets/issues/1674 | 777,321,840 | MDU6SXNzdWU3NzczMjE4NDA= | 1,674 | dutch_social can't be loaded | {
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"exactly the same issue in some other datasets.\r\nDid you find any solution??\r\n",
"Hi @koenvandenberge and @alighofrani95!\r\nThe datasets you're experiencing issues with were most likely added recently to the `datasets` library, meaning they have not been released yet. They will be released with the v2 of the... | 1,609,522,628,000 | 1,609,841,821,000 | null | NONE | null | Hi all,
I'm trying to import the `dutch_social` dataset described [here](https://huggingface.co/datasets/dutch_social).
However, the code that should load the data doesn't seem to be working, in particular because the corresponding files can't be found at the provided links.
```
(base) Koens-MacBook-Pro:~ koe... | {
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https://api.github.com/repos/huggingface/datasets/issues/1673 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1673/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1673/comments | https://api.github.com/repos/huggingface/datasets/issues/1673/events | https://github.com/huggingface/datasets/issues/1673 | 777,263,651 | MDU6SXNzdWU3NzcyNjM2NTE= | 1,673 | Unable to Download Hindi Wikipedia Dataset | {
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"Currently this dataset is only available when the library is installed from source since it was added after the last release.\r\n\r\nWe pin the dataset version with the library version so that people can have a reproducible dataset and processing when pinning the library.\r\n\r\nWe'll see if we can provide access ... | 1,609,498,373,000 | 1,609,842,132,000 | 1,609,842,132,000 | NONE | null | I used the Dataset Library in Python to load the wikipedia dataset with the Hindi Config 20200501.hi along with something called beam_runner='DirectRunner' and it keeps giving me the error that the file is not found. I have attached the screenshot of the error and the code both. Please help me to understand how to reso... | {
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https://api.github.com/repos/huggingface/datasets/issues/1672 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1672/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1672/comments | https://api.github.com/repos/huggingface/datasets/issues/1672/events | https://github.com/huggingface/datasets/issues/1672 | 777,258,941 | MDU6SXNzdWU3NzcyNTg5NDE= | 1,672 | load_dataset hang on file_lock | {
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"Can you try to upgrade to a more recent version of datasets?",
"Thank, upgrading to 1.1.3 resolved the issue.",
"Having the same issue with `datasets 1.1.3` of `1.5.0` (both tracebacks look the same) and `kilt_wikipedia`, Ubuntu 20.04\r\n\r\n```py\r\nIn [1]: from datasets import load_dataset ... | 1,609,496,707,000 | 1,617,207,853,000 | 1,609,501,656,000 | NONE | null | I am trying to load the squad dataset. Fails on Windows 10 but succeeds in Colab.
Transformers: 3.3.1
Datasets: 1.0.2
Windows 10 (also tested in WSL)
```
datasets.logging.set_verbosity_debug()
datasets.
train_dataset = load_dataset('squad', split='train')
valid_dataset = load_dataset('squad', split='validat... | {
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https://api.github.com/repos/huggingface/datasets/issues/1671 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1671/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1671/comments | https://api.github.com/repos/huggingface/datasets/issues/1671/events | https://github.com/huggingface/datasets/issues/1671 | 776,652,193 | MDU6SXNzdWU3NzY2NTIxOTM= | 1,671 | connection issue | {
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"Also, mayjor issue for me is the format issue, even if I go through changing the whole code to use load_from_disk, then if I do \r\n\r\nd = datasets.load_from_disk(\"imdb\")\r\nd = d[\"train\"][:10] => the format of this is no more in datasets format\r\nthis is different from you call load_datasets(\"train[10]\")\... | 1,609,365,380,000 | 1,609,754,391,000 | null | NONE | null | Hi
I am getting this connection issue, resulting in large failure on cloud, @lhoestq I appreciate your help on this.
If I want to keep the codes the same, so not using save_to_disk, load_from_disk, but save the datastes in the way load_dataset reads from and copy the files in the same folder the datasets library r... | {
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https://api.github.com/repos/huggingface/datasets/issues/1670 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1670/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1670/comments | https://api.github.com/repos/huggingface/datasets/issues/1670/events | https://github.com/huggingface/datasets/issues/1670 | 776,608,579 | MDU6SXNzdWU3NzY2MDg1Nzk= | 1,670 | wiki_dpr pre-processing performance | {
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"Hi ! And thanks for the tips :) \r\n\r\nIndeed currently `wiki_dpr` takes some time to be processed.\r\nMultiprocessing for dataset generation is definitely going to speed up things.\r\n\r\nRegarding the index note that for the default configurations, the index is downloaded instead of being built, which avoid spe... | 1,609,357,303,000 | 1,611,826,896,000 | null | NONE | null | I've been working with wiki_dpr and noticed that the dataset processing is seriously impaired in performance [1]. It takes about 12h to process the entire dataset. Most of this time is simply loading and processing the data, but the actual indexing is also quite slow (3h).
I won't repeat the concerns around multipro... | {
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https://api.github.com/repos/huggingface/datasets/issues/1669 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1669/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1669/comments | https://api.github.com/repos/huggingface/datasets/issues/1669/events | https://github.com/huggingface/datasets/issues/1669 | 776,608,386 | MDU6SXNzdWU3NzY2MDgzODY= | 1,669 | wiki_dpr dataset pre-processesing performance | {
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"Sorry, double posted."
] | 1,609,357,269,000 | 1,609,357,345,000 | 1,609,357,345,000 | NONE | null | I've been working with wiki_dpr and noticed that the dataset processing is seriously impaired in performance [1]. It takes about 12h to process the entire dataset. Most of this time is simply loading and processing the data, but the actual indexing is also quite slow (3h).
I won't repeat the concerns around multipro... | {
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https://api.github.com/repos/huggingface/datasets/issues/1662 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1662/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1662/comments | https://api.github.com/repos/huggingface/datasets/issues/1662/events | https://github.com/huggingface/datasets/issues/1662 | 775,890,154 | MDU6SXNzdWU3NzU4OTAxNTQ= | 1,662 | Arrow file is too large when saving vector data | {
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"Hi !\r\nThe arrow file size is due to the embeddings. Indeed if they're stored as float32 then the total size of the embeddings is\r\n\r\n20 000 000 vectors * 768 dimensions * 4 bytes per dimension ~= 60GB\r\n\r\nIf you want to reduce the size you can consider using quantization for example, or maybe using dimensi... | 1,609,248,192,000 | 1,611,238,359,000 | 1,611,238,359,000 | NONE | null | I computed the sentence embedding of each sentence of bookcorpus data using bert base and saved them to disk. I used 20M sentences and the obtained arrow file is about 59GB while the original text file is only about 1.3GB. Are there any ways to reduce the size of the arrow file? | {
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https://api.github.com/repos/huggingface/datasets/issues/1647 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1647/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1647/comments | https://api.github.com/repos/huggingface/datasets/issues/1647/events | https://github.com/huggingface/datasets/issues/1647 | 775,525,799 | MDU6SXNzdWU3NzU1MjU3OTk= | 1,647 | NarrativeQA fails to load with `load_dataset` | {
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"Hi @eric-mitchell,\r\nI think the issue might be that this dataset was added during the community sprint and has not been released yet. It will be available with the v2 of `datasets`.\r\nFor now, you should be able to load the datasets after installing the latest (master) version of `datasets` using pip:\r\n`pip i... | 1,609,179,369,000 | 1,609,848,308,000 | 1,609,696,685,000 | NONE | null | When loading the NarrativeQA dataset with `load_dataset('narrativeqa')` as given in the documentation [here](https://huggingface.co/datasets/narrativeqa), I receive a cascade of exceptions, ending with
FileNotFoundError: Couldn't find file locally at narrativeqa/narrativeqa.py, or remotely at
https://r... | {
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"Hover was added recently, that's why it wasn't available yet.\r\n\r\nTo load it you can just update `datasets`\r\n```\r\npip install --upgrade datasets\r\n```\r\n\r\nand then you can load `hover` with\r\n\r\n```python\r\nfrom datasets import load_dataset\r\n\r\ndataset = load_dataset(\"hover\")\r\n```"
] | 1,609,158,427,000 | 1,609,785,991,000 | null | NONE | null | Hi! I'm getting an error when trying to load **HoVeR** dataset. Another one (**SQuAD**) does work for me. I'm using the latest (1.1.3) version of the library.
Steps to reproduce the error:
```python
>>> from datasets import load_dataset
>>> dataset = load_dataset("hover")
Traceback (most recent call last):
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