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https://api.github.com/repos/huggingface/datasets/issues/2205 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2205/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2205/comments | https://api.github.com/repos/huggingface/datasets/issues/2205/events | https://github.com/huggingface/datasets/pull/2205 | 855,207,605 | MDExOlB1bGxSZXF1ZXN0NjEzMDAwMzYw | 2,205 | Updating citation information on LinCE readme | {
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"following_url"... | [] | 1,618,111,085,000 | 1,618,250,014,000 | 1,618,250,014,000 | CONTRIBUTOR | null | Hi!
I just updated the citation information in this PR. It had an additional bibtex from one of the datasets used in LinCE and then the LinCE bibtex. I removed the former and added a link that shows the full list of citations for each dataset.
Thanks! | {
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https://api.github.com/repos/huggingface/datasets/issues/2204 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2204/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2204/comments | https://api.github.com/repos/huggingface/datasets/issues/2204/events | https://github.com/huggingface/datasets/pull/2204 | 855,144,431 | MDExOlB1bGxSZXF1ZXN0NjEyOTU1MzM2 | 2,204 | Add configurable options to `seqeval` metric | {
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"following_url"... | [] | 1,618,084,699,000 | 1,618,494,586,000 | 1,618,494,586,000 | CONTRIBUTOR | null | Fixes #2148
Adds options to use strict mode, different schemes of evaluation, sample weight and adjust zero_division behavior, if encountered.
`seqeval` provides schemes as objects, hence dynamic import from string, to avoid making the user do the import (thanks to @albertvillanova for the `importlib` idea). | {
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https://api.github.com/repos/huggingface/datasets/issues/2203 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2203/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2203/comments | https://api.github.com/repos/huggingface/datasets/issues/2203/events | https://github.com/huggingface/datasets/pull/2203 | 855,053,595 | MDExOlB1bGxSZXF1ZXN0NjEyODg4MzA5 | 2,203 | updated banking77 train and test data | {
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"Hi ! Can you add a description regarding this PR ? Why do you think we need to update the dummy data used to test the `banking77` dataset loading script ?",
"Closing for inactivity. Feel free to re-open if you want to push this change"
] | 1,618,056,610,000 | 1,619,188,419,000 | 1,619,188,419,000 | NONE | null | {
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https://api.github.com/repos/huggingface/datasets/issues/2202 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2202/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2202/comments | https://api.github.com/repos/huggingface/datasets/issues/2202/events | https://github.com/huggingface/datasets/pull/2202 | 854,501,109 | MDExOlB1bGxSZXF1ZXN0NjEyNDM2ODMx | 2,202 | Add classes GenerateMode, DownloadConfig and Version to the documentation | {
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"following_url"... | [] | 1,617,973,099,000 | 1,618,250,280,000 | 1,618,250,279,000 | MEMBER | null | Add documentation for classes `GenerateMode`, `DownloadConfig` and `Version`.
Update the docstring of `load_dataset` to create cross-reference links to the classes.
Related to #2187. | {
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https://api.github.com/repos/huggingface/datasets/issues/2201 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2201/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2201/comments | https://api.github.com/repos/huggingface/datasets/issues/2201/events | https://github.com/huggingface/datasets/pull/2201 | 854,499,563 | MDExOlB1bGxSZXF1ZXN0NjEyNDM1NTE3 | 2,201 | Fix ArrowWriter overwriting features in ArrowBasedBuilder | {
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"following_url"... | [] | 1,617,972,979,000 | 1,618,234,337,000 | 1,618,234,336,000 | MEMBER | null | This should fix the issues with CSV loading experienced in #2153 and #2200.
The CSV builder is an ArrowBasedBuilder that had an issue with its ArrowWriter used to write the arrow file from the csv data.
The writer wasn't initialized with the features passed by the user. Therefore the writer was inferring the featur... | {
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https://api.github.com/repos/huggingface/datasets/issues/2200 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2200/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2200/comments | https://api.github.com/repos/huggingface/datasets/issues/2200/events | https://github.com/huggingface/datasets/issues/2200 | 854,449,656 | MDU6SXNzdWU4NTQ0NDk2NTY= | 2,200 | _prepare_split will overwrite DatasetBuilder.info.features | {
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"Hi ! This might be related to #2153 \r\n\r\nYou're right the ArrowWriter should be initialized with `features=self.info.features` ! Good catch\r\nI'm opening a PR to fix this and also to figure out how it was not caught in the tests\r\n\r\nEDIT: opened #2201",
"> Hi ! This might be related to #2153\r\n> \r\n> Yo... | 1,617,968,833,000 | 1,622,803,055,000 | 1,622,803,055,000 | NONE | null | Hi, here is my issue:
I initialized a Csv datasetbuilder with specific features:
```
def get_dataset_features(data_args):
features = {}
if data_args.text_features:
features.update({text_feature: hf_features.Value("string") for text_feature in data_args.text_features.strip().split(",")})
if da... | {
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https://api.github.com/repos/huggingface/datasets/issues/2199 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2199/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2199/comments | https://api.github.com/repos/huggingface/datasets/issues/2199/events | https://github.com/huggingface/datasets/pull/2199 | 854,417,318 | MDExOlB1bGxSZXF1ZXN0NjEyMzY0ODU3 | 2,199 | Fix backward compatibility in Dataset.load_from_disk | {
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"Hi @lhoestq, could you please check if this makes sense? Thanks.",
"What about using `_indices_data_files` field in save_to_disk instead of `_indices_files` ?\r\nThis way future datasets can also be reloaded from older versions of the lib\r\n\r\n`_indices_files` was introduced in a recent PR and was not released... | 1,617,966,070,000 | 1,617,983,825,000 | 1,617,983,825,000 | MEMBER | null | Fix backward compatibility when loading from disk an old dataset saved to disk with indices using key "_indices_data_files".
Related to #2195. | {
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https://api.github.com/repos/huggingface/datasets/issues/2198 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2198/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2198/comments | https://api.github.com/repos/huggingface/datasets/issues/2198/events | https://github.com/huggingface/datasets/pull/2198 | 854,357,481 | MDExOlB1bGxSZXF1ZXN0NjEyMzE0MTIz | 2,198 | added file_permission in load_dataset | {
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"From offline discussions: we want to make the permissions handling consistent with `transformers`. However from discussion in https://github.com/huggingface/transformers/pull/11119 it looks like it might not be a good solution to provide this argument. Users should use umask for now, and we'll see how things evol... | 1,617,961,146,000 | 1,618,582,306,000 | 1,618,582,306,000 | CONTRIBUTOR | null | As discussed in #2065 I've added `file_permission` argument in `load_dataset`.
Added mainly 2 things here:
1) Permission of downloaded datasets when converted to .arrow files can be changed with argument `file_permission` argument in `load_dataset` (default is 0o644 only)
2) Incase the user uses `map` later on t... | {
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`load_from_disk` was failing if there was no "_indices_files" field in state.json. This can happen if the dataset has no indices mapping | {
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"Hi ! Files that starts with `cache-*` are cached computation files, i.e. they are the cached results of map/filter/cast/etc. operations. For example if you used `map` on your dataset to transform it, then the resulting dataset is going to be stored and cached in a `cache-*` file. These files are used to avoid havi... | 1,617,940,159,000 | 1,618,205,129,000 | 1,618,205,129,000 | NONE | null | Hi,
I am using datasets to load large json file of 587G.
I checked the cached folder and found that there are two arrow files created:
* `cache-ed205e500a7dc44c.arrow` - 355G
* `json-train.arrow` - 582G
Why is the first file created?
If I delete it, would I still be able to `load_from_disk`? | {
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"Thanks for reporting @samsontmr.\r\n\r\nIt seems a backward compatibility issue...",
"Thanks @samsontmr this should be fixed on master now\r\n\r\nFeel free to reopen if you're still having issues"
] | 1,617,932,232,000 | 1,617,962,109,000 | 1,617,962,079,000 | NONE | null | After pulling the latest master, I'm getting a crash when `load_from_disk` tries to load my local dataset.
Trace:
```
Traceback (most recent call last):
File "load_data.py", line 11, in <module>
dataset = load_from_disk(SRC)
File "/opt/conda/envs/py38/lib/python3.8/site-packages/datasets/load.py", line ... | {
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"\r\nThis wasn't a `datasets` problem, but `transformers`' and it was solved here https://github.com/huggingface/transformers/pull/11168\r\n"
] | 1,617,915,768,000 | 1,617,987,410,000 | 1,617,933,177,000 | MEMBER | null | While this works fine with py3.8, under py3.7, with a totally new conda env and transformers install:
```
git clone https://github.com/huggingface/transformers
cd transformers
pip install -e .[testing]
export BS=1; rm -rf /tmp/test-clm; PYTHONPATH=src USE_TF=0 CUDA_VISIBLE_DEVICES=0 python \
examples/language... | {
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"Hi ! Yes we are working on making `filter` significantly faster. You can look at related PRs here: #2060 #2178 \r\n\r\nI think you can expect to have the fast version of `filter` available next week.\r\n\r\nWe'll make it only select one column, and we'll also make the overall filtering operation way faster by avoi... | 1,617,905,774,000 | 1,619,453,639,000 | 1,619,453,639,000 | CONTRIBUTOR | null | I'm currently using the `wikipedia` dataset— I'm tokenizing the articles with the `tokenizers` library using `map()` and also adding a new `num_tokens` column to the dataset as part of that map operation.
I want to be able to _filter_ the dataset based on this `num_tokens` column, but even when I specify `input_colu... | {
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The `packaging` dependency is also required for the build to complete. | {
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"I find very interesting that idea of using a fixture instead!\r\n\r\nLet me rework a little bit this PR, @lhoestq.",
"@lhoestq, as this is a big refactoring, I had many problems to solve the conflicts with the master branch...\r\n\r\nTherefore, I think it is better to merge this as it is, and then to make other ... | 1,617,880,864,000 | 1,618,818,791,000 | 1,618,818,790,000 | MEMBER | null | Refactorize Dataset tests to use Dataset as context manager. | {
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"Hi @anassalamah,\r\n\r\nCould you please try with this:\r\n```python\r\ntrain_ds = load_dataset(\"news_commentary\", lang1=\"ar\", lang2=\"en\", split='train[:98%]')\r\nval_ds = load_dataset(\"news_commentary\", lang1=\"ar\", lang2=\"en\", split='train[98%:]')\r\n```",
"Hello @albertvillanova, \r\n\r\nThanks for... | 1,617,868,423,000 | 1,621,850,635,000 | 1,621,850,635,000 | NONE | null | I used load_dataset to load the news_commentary dataset for "ar-en" translation pairs but found translations from Arabic to Hindi.
```
train_ds = load_dataset("news_commentary", "ar-en", split='train[:98%]')
val_ds = load_dataset("news_commentary", "ar-en", split='train[98%:]')
# filtering out examples that a... | {
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"Hi ! We refactored save_to_disk in #2025 so this doesn't happen.\r\nFeel free to try it on master for now\r\nWe'll do a new release soon"
] | 1,617,856,973,000 | 1,618,408,625,000 | null | NONE | null | As you can see, it saves the entire dataset.
@lhoestq
You can check by going through the following example,
```
from datasets import load_from_disk,concatenate_datasets
loaded_data=load_from_disk('/home/gsir059/HNSW-ori/my_knowledge_dataset')
n=20
kb_list=[loaded_data.shard(n, i, contiguous=True) for i... | {
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"Hi ! Thanks for reporting\r\nIf I recall correctly this has been recently fixed #1995\r\nCan you try to upgrade your local version of `datasets` ?\r\n```\r\npip install --upgrade datasets\r\n```",
"Hi Ihoestq,\r\n\r\nThank you. It works after upgrading the datasets\r\n"
] | 1,617,855,714,000 | 1,617,883,999,000 | 1,617,883,999,000 | NONE | null | I ran a simple code to list all texts in Timit dataset and the texts were all the same.
Is this dataset corrupted?
**Code:**
timit = load_dataset("timit_asr")
print(*timit['train']['text'], sep='\n')
**Result:**
Would such an act of refusal be useful?
Would such an act of refusal be useful?
Would such an act of... | {
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"An educated guess: does this refer to the fact that depending on the custom column names in the dataset files (csv in this case), there is a dataset loader being created? and this dataset loader - using the \"custom data configuration\" is used among all jobs running using this particular csv files? (thinking out ... | 1,617,840,988,000 | 1,618,412,158,000 | null | NONE | null | I thought I had disabled datasets caching in my code, as follows:
```
from datasets import set_caching_enabled
...
def main():
# disable caching in datasets
set_caching_enabled(False)
```
However, in my log files I see messages like the following:
```
04/07/2021 18:34:42 - WARNING - datasets.build... | {
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"cc @sebastiangehrmann"
] | 1,617,831,547,000 | 1,617,832,595,000 | 1,617,832,595,000 | MEMBER | null | This PR updates the GEM dataset to:
- remove extraneous fields in WikiAuto after https://github.com/huggingface/datasets/pull/2171 fixed the source
- add context and services to Schema Guided Dialog
- Add new or update challenge sets for MLSUM ES and DE, XSUM, and SGD | {
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"Hi, one workaround would be to save the mapped(tokenized in your case) file using `save_to_disk`, and having each process load this file using `load_from_disk`. This is what I am doing, and in this case, I turn off the ability to automatically load from the cache.\r\n\r\nAlso, multiprocessing the map function seem... | 1,617,819,734,000 | 1,634,973,075,000 | 1,617,982,711,000 | MEMBER | null | Hi,
I have a question regarding distributed training and the `.map` call on a dataset.
I have a local dataset "my_custom_dataset" that I am loading with `datasets = load_from_disk(dataset_path=my_path)`.
`dataset` is then tokenized:
```python
datasets = load_from_disk(dataset_path=my_path)
[...]
def tokeni... | {
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"Made the required changes @lhoestq , sorry it took so much time!"
] | 1,617,814,063,000 | 1,618,573,477,000 | 1,618,572,419,000 | CONTRIBUTOR | null | Addresses #2176
I'm happy to discuss the API and internals! | {
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"following_url"... | [] | 1,617,808,631,000 | 1,617,872,085,000 | 1,617,872,084,000 | MEMBER | null | Recently several changes happened:
1. latest versions of `fsspec` require python>3.7 for async features
2. `s3fs` added a dependency on `aiobotocore`, which is not compatible with the `moto` s3 mock context manager
This PR fixes both issues, by pinning `fsspec` and `s3fs` for python 3.6, and by using `moto` in ser... | {
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"I ping @krandiash to keep him up to date.",
"TODO:\r\n- [x] Add a section in the docs about this.\r\n- ~Add a warning if someone tries to specify `cache_file_name=` in `map`, `filter` etc. on a dataset that is in memory, since the computation is not going to be cached in this case.~",
"@lhoestq I have a questi... | 1,617,800,418,000 | 1,618,928,412,000 | 1,618,913,044,000 | MEMBER | null | Set a default value for `in_memory` depending on the size of the dataset to be loaded.
Close #2179.
TODO:
- [x] Add a section in the docs about this.
- ~Add a warning if someone tries to specify `cache_file_name=` in `map`, `filter` etc. on a dataset that is in memory, since the computation is not going to be c... | {
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https://api.github.com/repos/huggingface/datasets/issues/2181 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2181/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2181/comments | https://api.github.com/repos/huggingface/datasets/issues/2181/events | https://github.com/huggingface/datasets/issues/2181 | 852,261,607 | MDU6SXNzdWU4NTIyNjE2MDc= | 2,181 | Error when loading a HUGE json file (pyarrow.lib.ArrowInvalid: straddling object straddles two block boundaries) | {
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"Hi ! Can you try to increase the block size ? For example\r\n```python\r\nblock_size_10MB = 10<<20\r\nload_dataset(\"json\", ..., block_size=block_size_10MB)\r\n```\r\nThe block size corresponds to how much bytes to process at a time from the input stream.\r\nThis will determine multi-threading granularity as well... | 1,617,791,206,000 | 1,618,211,755,000 | 1,618,211,755,000 | NONE | null | Hi, thanks for the great library. I have used the brilliant library for a couple of small projects, and now using it for a fairly big project.
When loading a huge json file of 500GB, pyarrow complains as follows:
```
Traceback (most recent call last):
File "/home/user/.pyenv/versions/3.7.9/lib/python3.7/site-pack... | {
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https://api.github.com/repos/huggingface/datasets/issues/2179 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2179/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2179/comments | https://api.github.com/repos/huggingface/datasets/issues/2179/events | https://github.com/huggingface/datasets/issues/2179 | 852,237,957 | MDU6SXNzdWU4NTIyMzc5NTc= | 2,179 | Load small datasets in-memory instead of using memory map | {
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"following_url"... | [] | 1,617,789,496,000 | 1,618,913,044,000 | 1,618,913,043,000 | MEMBER | null | Currently all datasets are loaded using memory mapping by default in `load_dataset`.
However this might not be necessary for small datasets. If a dataset is small enough, then it can be loaded in-memory and:
- its memory footprint would be small so it's ok
- in-memory computations/queries would be faster
- the cach... | {
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"I addressed your comments about the docstrings and the output validation :)",
"I updated the bleurt mocking method and bleurt test is passing now.\r\nI also ran the slow tests and they are passing for bleurt.",
"Thanks @lhoestq and @albertvillanova !"
] | 1,617,787,850,000 | 1,618,928,444,000 | 1,618,306,096,000 | MEMBER | null | The `cast` operation on a pyarrow Table may create new arrays in memory.
This is an issue since users expect memory mapped datasets to not fill up the RAM.
To fix that I used `map` to write a new arrow file on disk when cast is used.
To make things more convenient I introduced the `arrow` formatting of a dataset, ... | {
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https://api.github.com/repos/huggingface/datasets/issues/2177 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2177/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2177/comments | https://api.github.com/repos/huggingface/datasets/issues/2177/events | https://github.com/huggingface/datasets/pull/2177 | 852,065,307 | MDExOlB1bGxSZXF1ZXN0NjEwMzc5MDYx | 2,177 | add social thumbnial | {
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"following_url"... | [] | 1,617,777,606,000 | 1,617,783,361,000 | 1,617,783,361,000 | MEMBER | null | # What does this PR do?
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https://api.github.com/repos/huggingface/datasets/issues/2176 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2176/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2176/comments | https://api.github.com/repos/huggingface/datasets/issues/2176/events | https://github.com/huggingface/datasets/issues/2176 | 851,865,795 | MDU6SXNzdWU4NTE4NjU3OTU= | 2,176 | Converting a Value to a ClassLabel | {
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"Hi @nelson-liu!\r\nHere is what I do to convert a string to class label:\r\n\r\n```python\r\nfrom datasets import load_dataset, features\r\n\r\n\r\ndset = load_dataset(...)\r\ncol_name = \"the string column name\"\r\n\r\nclass_names = dset.unique(col_name)\r\nclass_feature = features.ClassLabel(names=sorted(class... | 1,617,749,656,000 | 1,618,827,034,000 | null | NONE | null | Hi!
In the docs for `cast`, it's noted that `For non-trivial conversion, e.g. string <-> ClassLabel you should use map() to update the Dataset.`
Would it be possible to have an example that demonstrates such a string <-> ClassLabel conversion using `map`? Thanks! | {
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"Actually, I found the answer [here](https://github.com/facebookresearch/faiss/wiki/FAQ#what-does-it-mean-when-a-search-returns--1-ids). \r\n\r\nSo we have to do some modifications to the code for instances where the index doesn't retrieve any IDs.",
"@lhoestq @patrickvonplaten \r\n\r\nI also found another short... | 1,617,745,849,000 | 1,618,575,676,000 | 1,618,575,675,000 | NONE | null | I am working with RAG and playing around with different faiss indexes. At the moment I use **index = faiss.index_factory(768, "IVF65536_HNSW32,Flat")**.
During the retrieval phase exactly in [this line of retrieval_rag.py](https://github.com/huggingface/transformers/blob/master/src/transformers/models/rag/retrieval_... | {
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"following_url"... | [] | 1,617,712,820,000 | 1,617,713,753,000 | 1,617,713,753,000 | MEMBER | null | The latest release of docutils make the navbar in the documentation weird and the Markdown wrongly interpreted:
We had the same problem in Transformers and solved it by pinning docutils (a dep of sphinx... | {
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https://api.github.com/repos/huggingface/datasets/issues/2173 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2173/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2173/comments | https://api.github.com/repos/huggingface/datasets/issues/2173/events | https://github.com/huggingface/datasets/pull/2173 | 851,359,284 | MDExOlB1bGxSZXF1ZXN0NjA5Nzk2NzI2 | 2,173 | Add OpenSLR dataset | {
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"following_url"... | [] | 1,617,710,914,000 | 1,618,246,486,000 | 1,618,246,486,000 | CONTRIBUTOR | null | OpenSLR (https://openslr.org/) is a site devoted to hosting speech and language resources, such as training corpora for speech recognition, and software related to speech recognition. There are around 80 speech datasets listed in OpenSLR, currently this PR includes only 9 speech datasets SLR41, SLR42, SLR43, SLR44, SLR... | {
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https://api.github.com/repos/huggingface/datasets/issues/2172 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2172/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2172/comments | https://api.github.com/repos/huggingface/datasets/issues/2172/events | https://github.com/huggingface/datasets/pull/2172 | 851,229,399 | MDExOlB1bGxSZXF1ZXN0NjA5Njg4ODgx | 2,172 | Pin fsspec lower than 0.9.0 | {
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"following_url"... | [] | 1,617,700,749,000 | 1,617,702,567,000 | 1,617,702,566,000 | MEMBER | null | Today's release of `fsspec` 0.9.0 implied a new release of `s3fs` 0.6.0 but this version breaks the CI (see [here](https://app.circleci.com/pipelines/github/huggingface/datasets/5312/workflows/490f3240-cd1c-4dd1-bb60-b416771c5584/jobs/32734) for example)
I'm pinning `fsspec` until this has been resolved | {
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https://api.github.com/repos/huggingface/datasets/issues/2171 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2171/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2171/comments | https://api.github.com/repos/huggingface/datasets/issues/2171/events | https://github.com/huggingface/datasets/pull/2171 | 851,090,662 | MDExOlB1bGxSZXF1ZXN0NjA5NTY4MDcw | 2,171 | Fixed the link to wikiauto training data. | {
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"Also you can ignore the CI failing on `docs`, this has been fixed on master :)",
"@lhoestq I need to update other stuff on GEM later today too, so will merge this one and remove columns in the next PR!",
"Ok !"
] | 1,617,693,191,000 | 1,617,725,142,000 | 1,617,725,109,000 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/datasets/issues/2170 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2170/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2170/comments | https://api.github.com/repos/huggingface/datasets/issues/2170/events | https://github.com/huggingface/datasets/issues/2170 | 850,913,228 | MDU6SXNzdWU4NTA5MTMyMjg= | 2,170 | Wikipedia historic dumps are deleted but hf/datasets hardcodes dump date | {
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"It seems that this can be fixed from user's end by including a `date` argument, like this:\r\n\r\n`dataset = datasets.load_dataset('wikipedia', '20200501.en', date='20210420')`\r\n\r\nYou can get available dates from [here](https://dumps.wikimedia.org/enwiki/).\r\n\r\nThis is not a proper fix however as all the fi... | 1,617,678,798,000 | 1,623,805,850,000 | null | NONE | null | Wikimedia does not keep all historical dumps. For example, as of today https://dumps.wikimedia.org/kowiki/ only provides
```
20201220/ 02-Feb-2021 01:36 -
20210101/ 21-Feb-2021 01:26 -
20210120/ ... | {
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https://api.github.com/repos/huggingface/datasets/issues/2169 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2169/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2169/comments | https://api.github.com/repos/huggingface/datasets/issues/2169/events | https://github.com/huggingface/datasets/pull/2169 | 850,456,180 | MDExOlB1bGxSZXF1ZXN0NjA5MDI2ODUz | 2,169 | Updated WER metric implementation to avoid memory issues | {
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"Hi ! Thanks for suggesting this fix \r\nUnfortunately it looks like it's already been fixed by #2111 \r\n\r\nFeel free to share your thoughts about this PR !\r\n\r\nI'm closing this one if you don't mind."
] | 1,617,637,400,000 | 1,617,721,378,000 | 1,617,721,378,000 | NONE | null | This is in order to fix this issue:
https://github.com/huggingface/datasets/issues/2078
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https://api.github.com/repos/huggingface/datasets/issues/2168 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2168/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2168/comments | https://api.github.com/repos/huggingface/datasets/issues/2168/events | https://github.com/huggingface/datasets/pull/2168 | 849,957,941 | MDExOlB1bGxSZXF1ZXN0NjA4NjA4Nzg5 | 2,168 | Preserve split type when realoding dataset | {
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"Thanks for diving into this !\r\n\r\nBefore going further, I just want to make sure if using `eval` is the right solution\r\nPersonally I'm not a big fan of `eval` since it has many security concerns. Also storing string representations of python objects in the json files is not ideal either IMO, so maybe it's pos... | 1,617,569,181,000 | 1,618,829,825,000 | 1,618,823,335,000 | CONTRIBUTOR | null | Fixes #2167
Using `eval` is not ideal for security reasons (in web apps I assume), but without it the code would be much more complex IMO.
In terms of style, instead of explicitly importing a private member (`_RelativeInstruction`), we can add these imports at the top of the module:
```python
from . import arr... | {
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"following_url"... | [] | 1,617,564,594,000 | 1,618,823,335,000 | 1,618,823,335,000 | CONTRIBUTOR | null | A minimal reproducible example:
```python
>>> from datasets import load_dataset, Dataset
>>> dset = load_dataset("sst", split="train")
>>> dset.save_to_disk("sst")
>>> type(dset.split)
<class 'datasets.splits.NamedSplit'>
>>> dset = Dataset.load_from_disk("sst")
>>> type(dset.split) # NamedSplit expected
<cla... | {
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"Hi @vyraun ! The test references for CommonGen are not publicly available: you can reach out to the original dataset authors if you would like to ask for them, but we will not be releasing them as part of GEM (March 31st was the release date for the test set inputs, references are incidentally released for some of... | 1,617,501,765,000 | 1,617,696,792,000 | 1,617,696,792,000 | NONE | null | @yjernite Hi, are the test sets for the GEM datasets scheduled to be [added soon](https://gem-benchmark.com/shared_task)?
e.g.
```
from datasets import load_dataset
DATASET_NAME="common_gen"
data = load_dataset("gem", DATASET_NAME)
```
The test set doesn't have the target or references.
```
data['test... | {
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"Hi,\r\n\r\na HF dataset can be converted to a Torch Dataset with a simple wrapper as follows:\r\n```python\r\nfrom torch.utils.data import Dataset\r\n \r\nclass HFDataset(Dataset):\r\n def __init__(self, dset):\r\n self.dset = dset\r\n\r\n def __getitem__(self, idx):\r\n return self.dset[idx]\r... | 1,617,498,108,000 | 1,629,820,535,000 | 1,617,807,964,000 | NONE | null | Hi,
I'm trying to pretraine deep-speed model using HF arxiv dataset like:
```
train_ds = nlp.load_dataset('scientific_papers', 'arxiv')
train_ds.set_format(
type="torch",
columns=["input_ids", "attention_mask", "global_attention_mask", "labels"],
)
engine, _, _, _ = deepspeed.initialize(
... | {
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"following_url"... | [] | 1,617,484,022,000 | 1,617,720,069,000 | 1,617,720,068,000 | CONTRIBUTOR | null | Replaces all the occurrences of the `assertTrue(isinstance(` pattern with `assertIsInstance`. | {
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"Hi @mariosasko,\r\nJust came across this PR and I was wondering if we can use\r\n`description = \"\\n\\n\".join(OrderedDict.fromkeys([info.description for info in dataset_infos]))`\r\n\r\nThis will obviate the need for `unique` and is almost as fast as `set`. We could have used `dict` inplace of `OrderedDict` but ... | 1,617,460,290,000 | 1,617,720,000,000 | 1,617,719,999,000 | CONTRIBUTOR | null | I thought someone from the community with less experience would be interested in fixing this issue, but that wasn't the case.
Fixes #2103 | {
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"This looks like an issue with the cc100 dataset itself but not sure\r\nDid you try loading cc100 on your machine ?",
"Hi\nloading works fine, but the viewer only is broken\nthanks\n\nOn Wed, Apr 7, 2021 at 12:17 PM Quentin Lhoest ***@***.***>\nwrote:\n\n> This looks like an issue with the cc100 dataset itself bu... | 1,617,358,273,000 | 1,617,800,467,000 | null | NONE | null | Hi
visualization through dataset viewer for cc100 is broken
https://huggingface.co/datasets/viewer/
thanks a lot
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"Not yet but it’s on the short/mid-term roadmap (requested by many indeed).",
"oh, great, really awesome feature to have, thank you very much for the great, fabulous work",
"We'll work on dataset streaming soon. This should allow you to only load the examples you need ;)",
"thanks a lot Quentin, this would be... | 1,617,358,006,000 | 1,625,239,169,000 | null | NONE | null | Hi
Some of the datasets I need like cc100 are very large, and then I wonder if I can download first X samples of the shuffled/unshuffled data without going through first downloading the whole data then sampling? thanks | {
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"Hi.\r\nI cannot always reproduce this issue, and on later runs I did not see it so far. Sometimes also I set 8 processes but I see less being showed, is this normal, here only 5 are shown for 8 being set, thanks\r\n\r\n```\r\n#3: 11%|███████████████▊ ... | 1,617,350,173,000 | 1,617,358,472,000 | 1,617,358,471,000 | NONE | null | Hi @lhoestq
I am running this code from huggingface transformers https://github.com/huggingface/transformers/blob/master/examples/language-modeling/run_mlm.py
to speed up tokenization, since I am running on multiple datasets, I am using data_args.preprocessing_num_workers = 4 with opus100 corpus but this moves ... | {
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"closing since I think this is cc100, just the name has been changed. thanks "
] | 1,617,319,716,000 | 1,617,357,919,000 | 1,617,357,919,000 | NONE | null | ## Adding a Dataset
- **Name:** ccnet
- **Description:**
Common Crawl
- **Paper:**
https://arxiv.org/abs/1911.00359
- **Data:**
https://github.com/facebookresearch/cc_net
- **Motivation:**
this is one of the most comprehensive clean monolingual datasets across a variety of languages. Quite importan... | {
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"Thanks for reporting !\r\nThe viewer doesn't have all the dependencies of the datasets. We may add openpyxl to be able to show this dataset properly"
] | 1,617,286,400,000 | 1,617,791,169,000 | null | NONE | null | When I visit the [Huggingface - viewer](https://huggingface.co/datasets/viewer/) web site, under the dataset "fake_news_english" I've got this error:
> ImportError: To be able to use this dataset, you need to install the following dependencies['openpyxl'] using 'pip install # noqa: requires this pandas optional depe... | {
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"Just note that docstrings injected from PyArrow do not follow the same convention for formatting types in `Args` or `Returns` as we do... Not a big problem, anyway! 😄 "
] | 1,617,201,370,000 | 1,617,295,590,000 | 1,617,205,328,000 | MEMBER | null | Following #2025 , I added the table classes to the documentation
cc @albertvillanova | {
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"Awesome!"
] | 1,617,200,570,000 | 1,617,269,220,000 | 1,617,268,568,000 | CONTRIBUTOR | null | NorNE is a manually annotated corpus of named entities which extends the annotation of the existing Norwegian Dependency Treebank. Comprising both of the official standards of written Norwegian (Bokmål and Nynorsk), the corpus contains around 600,000 tokens and annotates a rich set of entity types including persons, or... | {
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"Hi ! Thanks for reporting. I opened a PR to fix this issue: #2201",
"Nice question which helped me a lot! I have wasted a lot of time to the `DatasetDict` creation from a csv file. Hope the document of this module add some simple examples.",
"Hi :) We're indeed working on tutorials that we will add to the docs... | 1,617,179,409,000 | 1,630,077,838,000 | null | NONE | null | First of all, I'm sorry if it is a repeated issue or the changes are already in master, I searched and I didn't find anything.
I'm using datasets 1.5.0
As you can see, when I load the dataset, the C... | {
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"@lhoestq I am going to implement the consolidation step you mentioned in #1870.",
"@lhoestq I was thinking that the order of the TableBlocks is not relevant, isn't it?\r\n\r\nI mean, in order to consolidate _consecutive_ in-memory table blocks, in this case:\r\n```\r\nblocks = [in_memory_1, memory_mapped, in_mem... | 1,617,123,524,000 | 1,624,470,062,000 | 1,618,848,438,000 | MEMBER | null | Add support for `axis` (0 or 1) in `concatenate_datasets`.
Close #853. | {
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"following_url"... | [] | 1,617,119,516,000 | 1,617,187,035,000 | 1,617,187,034,000 | MEMBER | null | This should fix issue #2134
Pickling is limited to <4GiB objects, it's not possible to pickle a big arrow table (for multiprocessing for example).
For big tables, we have to write them on disk and only pickle the path to the table. | {
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"Good catch ! Thanks for reporting\r\n\r\nI just opened #2180 to fix this"
] | 1,617,117,994,000 | 1,617,791,015,000 | null | CONTRIBUTOR | null | from nlp import load_dataset
train_dataset = load_dataset('xtreme', 'tatoeba.tel')['validation']
ValueError: BuilderConfig tatoeba.tel not found.
but language tel is actually included in xtreme:
https://github.com/google-research/xtreme/blob/master/utils_preprocess.py
def tatoeba_preprocess(args):
lang3_dict ... | {
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"Hi @marrodion. \r\n\r\nThanks for pointing this out. It would be great to incorporate this metric-specific enhancement.\r\n\r\nAnother possibility would be to require the user to input the scheme as a string `mode=\"strict\", scheme=\"IOB2\"` and then dynamically import the corresponding module using Python `impor... | 1,617,116,646,000 | 1,618,494,586,000 | 1,618,494,586,000 | CONTRIBUTOR | null | Right now `load_metric("seqeval")` only works in the default mode of evaluation (equivalent to conll evaluation).
However, seqeval library [supports](https://github.com/chakki-works/seqeval#support-features) different evaluation schemes (IOB1, IOB2, etc.), which can be plugged in just by supporting additional kwargs... | {
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"following_url"... | [] | 1,617,116,143,000 | 1,617,196,265,000 | 1,617,196,265,000 | MEMBER | null | This documentation setting will avoid having the return type in a separate line under `Return type`.
See e.g. current docs for `Dataset.to_csv`. | {
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"Hi ! In the arrow file we store all the integers as uint8.\r\nSo your arrow file should weigh around `height x width x n_channels x n_images` bytes.\r\n\r\nWhat feature type do your TFDS dataset have ?\r\n\r\nIf it uses a `tfds.features.Image` type, then what is stored is the encoded data (as png or jpg for exampl... | 1,617,115,569,000 | 1,618,578,422,000 | null | NONE | null | Hi,
I have created my own dataset using the provided dataset loading script. It is an image dataset where images are stored as 3D Array with dtype=uint8.
The actual size on disk is surprisingly large. It takes 520 MB. Here is some info from `dataset_info.json`.
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"#2274 has been merged. You can now merge master into this branch and use `assert_arrow_metadata_are_synced_with_dataset_features(dset)` to make sure that the metadata are good :)"
] | 1,617,112,934,000 | 1,619,707,844,000 | 1,619,707,843,000 | MEMBER | null | Implement `Dataset.add_column`.
Close #1954. | {
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"That's how I loaded the dataset\r\n```python\r\nfrom datasets import load_dataset\r\nds = load_dataset('wikipedia', '20200501.en', cache_dir='/usr/local/workspace/NAS_NLP/cache')\r\n```",
"Hi ! It looks like the arrow file in the folder\r\n`/usr/local/workspace/NAS_NLP/cache/wikipedia/20200501.en/1.0.0/50aa706aa... | 1,617,100,711,000 | 1,617,268,877,000 | null | NONE | null | **Problem description**
I am getting the following error when trying to load wikipedia/20200501.en dataset.
**Error log**
Downloading and preparing dataset wikipedia/20200501.en (download: 16.99 GiB, generated: 17.07 GiB, post-processed: Unknown size, total: 34.06 GiB) to /usr/local/workspace/NAS_NLP/cache/wikiped... | {
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not satisfied with the API, it means as a dataset implementer I need to write a function with boilerplate and write classes for each `<dataset><task>` "facet". | {
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"following_url"... | [] | 1,617,061,622,000 | 1,617,063,002,000 | 1,617,063,002,000 | MEMBER | null | This branch updates the GEM benchmark to its 1.1 version which includes:
- challenge sets for most tasks
- detokenized TurkCorpus to match the rest of the text simplification subtasks
- fixed inputs for TurkCorpus and ASSET test sets
- 18 languages in WikiLingua
cc @sebastianGehrmann | {
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"Hi @lhoestq \r\nThanks a lot for taking time checking it. I update \"dataset_infos.json\", I added description to the function of _generate_samples in wikiann.py but I was not sure about the format to write in README. thanks. ",
"Thanks !\r\n\r\nFor the fields description in the dataset card, something like thi... | 1,617,061,106,000 | 1,617,197,270,000 | 1,617,197,270,000 | CONTRIBUTOR | null | Hi @lhoestq
I tried to add spans to the wikiann datasets.
Thanks a lot for kindly having a look.
This addresses https://github.com/huggingface/datasets/issues/2130.
Best regards
Rabeeh | {
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"@lhoestq I updated files"
] | 1,617,053,543,000 | 1,617,960,738,000 | 1,617,960,738,000 | CONTRIBUTOR | null | Intent classification/detection dataset from banking category with 77 unique intents. | {
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"Hi !\r\nI think this has been fixed recently on `master`.\r\nCan you try again by installing `datasets` from `master` ?\r\n```\r\npip install git+https://github.com/huggingface/datasets.git\r\n```",
"Hi!\r\n\r\nUsing that version of the code solves the issue. Thanks!"
] | 1,617,042,234,000 | 1,617,095,573,000 | 1,617,095,573,000 | NONE | null | Hi,
Loading a dataset with `load_dataset` using a split defined via `ReadInstruction` and then saving it to disk results in the following error: `TypeError: Object of type ReadInstruction is not JSON serializable`.
Here is the minimal reproducible example:
```python
from datasets import load_dataset
from dat... | {
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"following_url"... | [] | 1,617,033,147,000 | 1,617,725,771,000 | 1,617,693,278,000 | CONTRIBUTOR | null | Add Character Error Rate (CER) metric that is used in evaluation in ASR. I also have written unittests (hopefully thorough enough) but I'm not sure how to integrate them into the existed codebase.
```python
from cer import CER
cer = CER()
class TestCER(unittest.TestCase):
def test_cer_case_senstive(self)... | {
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"following_url"... | [] | 1,617,032,772,000 | 1,617,186,956,000 | 1,617,186,955,000 | MEMBER | null | This should fix issue #2131
When calling `load_dataset` at the same time from 2 workers, one of the worker could have missing split infos when reloading the dataset from the cache.
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"Hi ! Indeed only the languages of the `translate-train` data are included...\r\nI can't find a link to download the english train set on https://github.com/facebookresearch/MLQA though, do you know where we can download it ?",
"Hi @lhoestq \r\nthank you very much for coming back to me, now I see, you are right, ... | 1,617,014,870,000 | 1,617,099,623,000 | 1,617,099,623,000 | CONTRIBUTOR | null | Hi
I need mlqa-translate-train.en dataset, but it is missing from the MLQA dataset. could you have a look please? @lhoestq thank you for your help to fix this issue. | {
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"Hi !\r\nIndeed `save_to_disk` doesn't call pickle anymore. Though the `OverflowError` can still appear for in-memory datasets bigger than 4GB. This happens when doing this for example:\r\n```python\r\nimport pyarrow as pa\r\nimport pickle\r\n\r\narr = pa.array([0] * ((4 * 8 << 30) // 64))\r\ntable = pa.Table.from_... | 1,617,014,595,000 | 1,620,064,761,000 | 1,620,064,761,000 | NONE | null | Using Datasets 1.5.0 on Python 3.7.
Recently I've been working on medium to large size datasets (pretokenized raw text sizes from few gigabytes to low tens of gigabytes), and have found out that several preprocessing steps are massively faster when done in memory, and I have the ability to requisition a lot of RAM, so... | {
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"If you print those questions, you get readable texts:\r\n```python\r\n>>> questions = [\r\n... \"\\u0645\\u062a\\u0649 \\u0628\\u062f\\u0627\\u062a \\u0627\\u0644\\u0645\\u062c\\u0644\\u0629 \\u0627\\u0644\\u0645\\u062f\\u0631\\u0633\\u064a\\u0629 \\u0641\\u064a \\u0646\\u0648\\u062a\\u0631\\u062f\\u0627\\u064... | 1,617,008,589,000 | 1,617,126,057,000 | 1,617,126,057,000 | NONE | null | Hi
Looking into MLQA dataset for langauge "ar":
```
"question": [
"\u0645\u062a\u0649 \u0628\u062f\u0627\u062a \u0627\u0644\u0645\u062c\u0644\u0629 \u0627\u0644\u0645\u062f\u0631\u0633\u064a\u0629 \u0641\u064a \u0646\u0648\u062a\u0631\u062f\u0627\u0645 \u0628\u0627\u0644\u0646\u0634\u0631?",
"\u0643\u0... | {
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"You can filter the languages this way:\r\n```python\r\ntydiqa_en = tydiqa_dataset.filter(lambda x: x[\"language\"] == \"english\")\r\n```\r\n\r\nOtherwise maybe we can have one configuration per language ?\r\nWhat do you think of this for example ?\r\n\r\n```python\r\nload_dataset(\"tydiqa\", \"primary_task.en\")\... | 1,617,008,181,000 | 1,617,530,235,000 | null | NONE | null | Hi @lhoestq
Currently TydiQA is mixed and user can only access the whole training set of all languages:
https://www.tensorflow.org/datasets/catalog/tydi_qa
for using this dataset, one need to train/evaluate in each separate language, and having them mixed, makes it hard to use this dataset. This is much convenien... | {
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"Hi ! Thanks for reporting\r\nI was able to reproduce this issue. This was caused by missing split infos if a worker reloads the cache of the other worker.\r\n\r\nI just opened https://github.com/huggingface/datasets/pull/2137 to fix this issue",
"The PR got merged :)\r\nFeel free to try it out on the `master` br... | 1,617,007,558,000 | 1,618,052,935,000 | 1,618,052,935,000 | NONE | null | version: 1.5.0
met a very strange error, I am training large scale language model, and need train on 2 machines(workers).
And sometimes I will get this error `TypeError: 'NoneType' object is not iterable`
This is traceback
```
71 | | Traceback (most recent call last):
-- | -- | --
72 | | File "run_gpt.py"... | {
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"Here please find TFDS format of this dataset: https://www.tensorflow.org/datasets/catalog/wikiann\r\nwhere there is a span column, this is really necessary to be able to use the data, and I appreciate your help @lhoestq ",
"Hi !\r\nApparently you can get the spans from the NER tags using `tags_to_spans` defined ... | 1,617,006,180,000 | 1,630,075,458,000 | 1,630,075,458,000 | NONE | null | Hi
Wikiann dataset needs to have "spans" columns, which is necessary to be able to use this dataset, but this column is missing from huggingface datasets, could you please have a look? thank you @lhoestq | {
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"Hi !\r\nWe're not using `TextDatasetForNextSentencePrediction` in `datasets`.\r\nAlthough you can probably use the `TextDatasetForNextSentencePrediction.create_examples_from_document` on a dataset to prepare it for next sentence prediction.",
"Thanks.\r\n\r\nDo you mean that `TextDatasetForNextSentencePrediction... | 1,617,000,483,000 | 1,617,253,120,000 | 1,617,253,120,000 | NONE | null | Hello.
I'm trying to pretrain the BERT model with next sentence prediction. Is there any function that supports next sentence prediction
like ` TextDatasetForNextSentencePrediction` of `huggingface/transformers` ?
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"Hi\r\nGood catch ! Thanks for reporting\r\n\r\nIf you are interested in contributing, feel free to open a PR to fix this :) "
] | 1,616,999,642,000 | 1,617,194,881,000 | 1,617,194,881,000 | CONTRIBUTOR | null | Hi @yjernite, thank you for adding MultiWoZ 2.2 in the huggingface datasets platform. It is beneficial!
I spot an error that the order of Dialogue action slot names and values are reversed.
https://github.com/huggingface/datasets/blob/649b2c469779bc4221e1b6969aa2496d63eb5953/datasets/multi_woz_v22/multi_woz_v22.p... | {
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https://api.github.com/repos/huggingface/datasets/issues/2127 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2127/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2127/comments | https://api.github.com/repos/huggingface/datasets/issues/2127/events | https://github.com/huggingface/datasets/pull/2127 | 843,017,199 | MDExOlB1bGxSZXF1ZXN0NjAyNDYxMzc3 | 2,127 | make documentation more clear to use different cloud storage | {
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"following_url"... | [] | 1,616,999,046,000 | 1,617,020,184,000 | 1,617,020,184,000 | MEMBER | null | This PR extends the cloud storage documentation. To show you can use a different `fsspec` implementation. | {
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"following_url"... | [] | 1,616,950,650,000 | 1,617,010,034,000 | 1,617,010,033,000 | CONTRIBUTOR | null | The title says it all (motivated by [this issue](https://github.com/pytorch/pytorch/issues/53146) in the pytorch repo). | {
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https://api.github.com/repos/huggingface/datasets/issues/2125 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2125/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2125/comments | https://api.github.com/repos/huggingface/datasets/issues/2125/events | https://github.com/huggingface/datasets/issues/2125 | 842,690,570 | MDU6SXNzdWU4NDI2OTA1NzA= | 2,125 | Is dataset timit_asr broken? | {
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"Hi,\r\n\r\nthanks for the report, but this is a duplicate of #2052. ",
"@mariosasko \r\nThank you for your quick response! Following #2052, I've fixed the problem."
] | 1,616,920,218,000 | 1,616,934,565,000 | 1,616,934,565,000 | NONE | null | Using `timit_asr` dataset, I saw all records are the same.
``` python
from datasets import load_dataset, load_metric
timit = load_dataset("timit_asr")
from datasets import ClassLabel
import random
import pandas as pd
from IPython.display import display, HTML
def show_random_elements(dataset, num_example... | {
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https://api.github.com/repos/huggingface/datasets/issues/2124 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2124/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2124/comments | https://api.github.com/repos/huggingface/datasets/issues/2124/events | https://github.com/huggingface/datasets/issues/2124 | 842,627,729 | MDU6SXNzdWU4NDI2Mjc3Mjk= | 2,124 | Adding ScaNN library to do MIPS? | {
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"I haven't played with it (yet) but it sounds really cool !\r\n"
] | 1,616,890,020,000 | 1,617,024,223,000 | null | NONE | null | @lhoestq Hi I am thinking of adding this new google library to do the MIPS similar to **add_faiss_idex**. As the paper suggests, it is really fast when it comes to retrieving the nearest neighbors.
https://github.com/google-research/google-research/tree/master/scann
![image](https://user-images.githubusercontent... | {
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https://api.github.com/repos/huggingface/datasets/issues/2123 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2123/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2123/comments | https://api.github.com/repos/huggingface/datasets/issues/2123/events | https://github.com/huggingface/datasets/issues/2123 | 842,577,285 | MDU6SXNzdWU4NDI1NzcyODU= | 2,123 | Problem downloading GEM wiki_auto_asset_turk dataset | {
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"Hi,\r\n\r\nsadly I can't replicate the problem on my Windows machine. Try to update the library to the newest version with:\r\n```bash\r\npip install git+https://github.com/huggingface/datasets\r\n``` ",
"Thanks for the answer! I updated the library but unfortunately it didn't solve the problem.",
"Is there an... | 1,616,870,488,000 | 1,620,836,118,000 | 1,620,836,117,000 | NONE | null | @yjernite
### Summary
I am currently working on the GEM datasets and do not manage to download the wiki_auto_asset_turk data, whereas all other datasets download well with the same code.
### Steps to reproduce
Code snippet:
from datasets import load_dataset
#dataset = load_dataset('gem', 'web_nlg_en')
d... | {
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https://api.github.com/repos/huggingface/datasets/issues/2122 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2122/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2122/comments | https://api.github.com/repos/huggingface/datasets/issues/2122/events | https://github.com/huggingface/datasets/pull/2122 | 842,194,588 | MDExOlB1bGxSZXF1ZXN0NjAxODE3MjI0 | 2,122 | Fast table queries with interpolation search | {
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"following_url"... | [] | 1,616,782,160,000 | 1,628,100,719,000 | 1,617,719,581,000 | MEMBER | null | ## Intro
This should fix issue #1803
Currently querying examples in a dataset is O(n) because of the underlying pyarrow ChunkedArrays implementation.
To fix this I implemented interpolation search that is pretty effective since datasets usually verifies the condition of evenly distributed chunks (the default ch... | {
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https://api.github.com/repos/huggingface/datasets/issues/2121 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2121/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2121/comments | https://api.github.com/repos/huggingface/datasets/issues/2121/events | https://github.com/huggingface/datasets/pull/2121 | 842,148,633 | MDExOlB1bGxSZXF1ZXN0NjAxNzc4NDc4 | 2,121 | Add Validation For README | {
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"Good start! Here are some proposed next steps:\r\n- We want the Class structure to reflect the template - so the parser know what section titles to expect and when something has gone wrong\r\n- As a result, we don't need to parse the table of contents, since it will always be the same\r\n- For each section/subsect... | 1,616,778,137,000 | 1,620,652,638,000 | 1,620,639,701,000 | CONTRIBUTOR | null | Hi @lhoestq, @yjernite
This is a simple Readme parser. All classes specific to different sections can inherit `Section` class, and we can define more attributes in each.
Let me know if this is going in the right direction :)
Currently the output looks like this, for `to_dict()` on `FashionMNIST` `README.md`:
... | {
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https://api.github.com/repos/huggingface/datasets/issues/2120 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2120/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2120/comments | https://api.github.com/repos/huggingface/datasets/issues/2120/events | https://github.com/huggingface/datasets/issues/2120 | 841,954,521 | MDU6SXNzdWU4NDE5NTQ1MjE= | 2,120 | dataset viewer does not work anymore | {
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"Thanks for reporting :) We're looking into it",
"Back up. "
] | 1,616,764,933,000 | 1,616,773,942,000 | 1,616,773,942,000 | NONE | null | Hi
I normally use this link to see all datasets and how I can load them
https://huggingface.co/datasets/viewer/
Now I am getting
502 Bad Gateway
nginx/1.18.0 (Ubuntu)
could you bring this webpage back ? this was very helpful @lhoestq
thanks for your help | {
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https://api.github.com/repos/huggingface/datasets/issues/2119 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2119/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2119/comments | https://api.github.com/repos/huggingface/datasets/issues/2119/events | https://github.com/huggingface/datasets/pull/2119 | 841,567,199 | MDExOlB1bGxSZXF1ZXN0NjAxMjg2MjIy | 2,119 | copy.deepcopy os.environ instead of copy | {
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"following_url"... | [] | 1,616,731,118,000 | 1,616,771,632,000 | 1,616,771,632,000 | CONTRIBUTOR | null | Fixes: https://github.com/huggingface/datasets/issues/2115
- bug fix: using envrion.copy() returns a dict.
- using deepcopy(environ) returns an `_environ` object
- Changing the datatype of the _environ object can break code, if subsequent libraries perform operations using apis exclusive to the environ object, lik... | {
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"I thought deepcopy on `os.environ` is unsafe (see [this](https://stackoverflow.com/questions/13142972/using-copy-deepcopy-on-os-environ-in-python-appears-broken)), but I can't replicate the behavior described in the linked SO thread.\r\n\r\nClosing this one because #2119 has a much cleaner approach."
] | 1,616,730,497,000 | 1,616,760,203,000 | 1,616,760,005,000 | CONTRIBUTOR | null | Replace `os.environ.copy` with in-place modification
Fixes #2115 | {
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"@Frankie123421 what was the resolution to this?",
"> @Frankie123421 what was the resolution to this?\r\n\r\nuse glue_metric.py instead of glue.py in load_metric",
"thank you!"
] | 1,616,726,122,000 | 1,629,927,845,000 | 1,616,726,426,000 | NONE | null | actual_task = "mnli" if task == "mnli-mm" else task
dataset = load_dataset(path='/home/glue.py', name=actual_task)
metric = load_metric(path='/home/glue.py', name=actual_task)
---------------------------------------------------------------------------
TypeError Traceback (most recent... | {
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"Hi,\r\n\r\nthe `_data` attribute is missing due to `MyDataset.__init__` not calling the parent `__init__`. However, I don't think it's a good idea to subclass the `datasets.Dataset` class (e.g. it's kind of dangerous to override `datasets.Dataset.__getitem__`). Instead, it's better to follow the \"association over... | 1,616,719,066,000 | 1,617,201,032,000 | 1,617,201,032,000 | NONE | null | calling `map()` of `datasets` library results into an error while defining a Custom dataset.
Reproducible example:
```
import datasets
class MyDataset(datasets.Dataset):
def __init__(self, sentences):
"Initialization"
self.samples = sentences
def __len__(self):
"Denotes the ... | {
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"following_url"... | [] | 1,616,704,159,000 | 1,616,771,632,000 | 1,616,771,632,000 | NONE | null | In our testing, we noticed that the datasets.map() implementation is modifying the datatype of python os.environ object from '_Environ' to 'dict'.
This causes following function calls to fail as follows:
`
x = os.environ.get("TEST_ENV_VARIABLE_AFTER_dataset_map", default=None)
TypeError: get() takes... | {
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"> Awesome thank you :)\r\n> This is really cool\r\n> \r\n> I left a few comments.\r\n> \r\n> Also it looks like the dummy data are quite big (100-200KB each). Can you try to reduce their sizes please ? For example I noticed that all the jsonl files inside the `dummy_data.zip` files have 20 lines. Can you only keep... | 1,616,697,617,000 | 1,617,187,130,000 | 1,617,187,130,000 | CONTRIBUTOR | null | Add support for two legal NLP datasets:
- EURLEX (https://www.aclweb.org/anthology/P19-1636/)
- ECtHR cases (https://arxiv.org/abs/2103.13084)
- EU-REG-IR (https://arxiv.org/abs/2101.10726) | {
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This will avoid
> During handling of the above exception, another exception occurred: | {
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"following_url"... | [] | 1,616,689,457,000 | 1,616,697,571,000 | 1,616,697,271,000 | CONTRIBUTOR | null | Add support for two legal NLP datasets:
- EURLEX (https://www.aclweb.org/anthology/P19-1636/)
- ECtHR cases (https://arxiv.org/abs/2103.13084) | {
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https://api.github.com/repos/huggingface/datasets/issues/2111 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2111/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2111/comments | https://api.github.com/repos/huggingface/datasets/issues/2111/events | https://github.com/huggingface/datasets/pull/2111 | 841,082,087 | MDExOlB1bGxSZXF1ZXN0NjAwODY4OTg5 | 2,111 | Compute WER metric iteratively | {
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"I discussed with Patrick and I think we could have a nice addition: have a parameter `concatenate_texts` that, if `True`, uses the old implementation.\r\n\r\nBy default `concatenate_texts` would be `False`, so that sentences are evaluated independently, and to save resources (the WER computation has a quadratic co... | 1,616,688,408,000 | 1,617,693,643,000 | 1,617,693,643,000 | MEMBER | null | Compute WER metric iteratively to avoid MemoryError.
Fix #2078. | {
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"Hi ! The SplitInfo is not always available. By default you would get `split_info.num_examples == 0`\r\nSo unfortunately we can't use this assertion you suggested",
"> Hi ! The SplitInfo is not always available. By default you would get `split_info.num_examples == 0`\r\n> So unfortunately we can't use this assert... | 1,616,668,760,000 | 1,618,234,383,000 | 1,618,234,383,000 | CONTRIBUTOR | null | Fix incorrect num_examples comparison assertion in builder.py | {
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https://api.github.com/repos/huggingface/datasets/issues/2109 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2109/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2109/comments | https://api.github.com/repos/huggingface/datasets/issues/2109/events | https://github.com/huggingface/datasets/pull/2109 | 840,746,598 | MDExOlB1bGxSZXF1ZXN0NjAwNTg1MzM5 | 2,109 | Add more issue templates and customize issue template chooser | {
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"If you agree, I could also add a link to [Discussions](https://github.com/huggingface/datasets/discussions) in order to reinforce the use of Discussion to make Questions (instead of Issues).\r\n\r\nI could also add some other templates: Bug, Feature Request,...",
"@theo-m we wrote our same comments at the same t... | 1,616,665,313,000 | 1,618,813,211,000 | 1,618,813,211,000 | MEMBER | null | When opening an issue, it is not evident for the users how to choose a blank issue template. There is a link at the bottom of all the other issue templates (`Don’t see your issue here? Open a blank issue.`), but this is not very visible for users. This is the reason why many users finally chose the `add-dataset` templa... | {
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https://api.github.com/repos/huggingface/datasets/issues/2108 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2108/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2108/comments | https://api.github.com/repos/huggingface/datasets/issues/2108/events | https://github.com/huggingface/datasets/issues/2108 | 840,181,055 | MDU6SXNzdWU4NDAxODEwNTU= | 2,108 | Is there a way to use a GPU only when training an Index in the process of add_faisis_index? | {
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"following_url"... | [] | 1,616,621,536,000 | 1,616,653,903,000 | null | NONE | null | Motivation - Some FAISS indexes like IVF consist of the training step that clusters the dataset into a given number of indexes. It would be nice if we can use a GPU to do the training step and covert the index back to CPU as mention in [this faiss example](https://gist.github.com/mdouze/46d6bbbaabca0b9778fca37ed2bcccf6... | {
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https://api.github.com/repos/huggingface/datasets/issues/2107 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2107/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2107/comments | https://api.github.com/repos/huggingface/datasets/issues/2107/events | https://github.com/huggingface/datasets/pull/2107 | 839,495,825 | MDExOlB1bGxSZXF1ZXN0NTk5NTAxODE5 | 2,107 | Metadata validation | {
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"> Also I was wondering this is really needed to have `utils.metadata` as a submodule of `datasets` ? This is only used by the CI so I'm not sure we should have this in the actual `datasets` package.\r\n\r\nI'm unclear on the suggestion, would you rather have a root-level `./metadata.py` file? I think it's well whe... | 1,616,575,961,000 | 1,619,425,634,000 | 1,619,425,633,000 | CONTRIBUTOR | null | - `pydantic` metadata schema with dedicated validators against our taxonomy
- ci script to validate new changes against this schema and start a vertuous loop
- soft validation on tasks ids since we expect the taxonomy to undergo some changes in the near future
for reference with the current validation we have ~365... | {
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https://api.github.com/repos/huggingface/datasets/issues/2106 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/2106/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/2106/comments | https://api.github.com/repos/huggingface/datasets/issues/2106/events | https://github.com/huggingface/datasets/issues/2106 | 839,084,264 | MDU6SXNzdWU4MzkwODQyNjQ= | 2,106 | WMT19 Dataset for Kazakh-English is not formatted correctly | {
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"Hi ! Thanks for reporting\r\n\r\nBy looking at the raw `news-commentary-v14.en-kk.tsv` file, it looks like there are at least 17 lines with this issue.\r\nMoreover these issues are not always the same:\r\n- L97 is only `kk` text and must be appended at the end of the `kk` text of the **next** line\r\n- L2897 is on... | 1,616,530,487,000 | 1,616,708,180,000 | null | NONE | null | In addition to the bug of languages being switched from Issue @415, there are incorrect translations in the dataset because the English-Kazakh translations have a one off formatting error.
The News Commentary v14 parallel data set for kk-en from http://www.statmt.org/wmt19/translation-task.html has a bug here:
> ... | {
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