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https://api.github.com/repos/huggingface/datasets/issues/422 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/422/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/422/comments | https://api.github.com/repos/huggingface/datasets/issues/422/events | https://github.com/huggingface/datasets/pull/422 | 663,028,497 | MDExOlB1bGxSZXF1ZXN0NDU0NTE3MDU2 | 422 | - Corrected encoding for IMDB. | {
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} | The preparation phase (after the download phase) crashed on windows because of charmap encoding not being able to decode certain characters. This change suggested in Issue #347 fixes it for the IMDB dataset. | https://api.github.com/repos/huggingface/datasets/issues/422/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/421 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/421/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/421/comments | https://api.github.com/repos/huggingface/datasets/issues/421/events | https://github.com/huggingface/datasets/pull/421 | 662,213,864 | MDExOlB1bGxSZXF1ZXN0NDUzNzkzMzQ1 | 421 | Style change | {
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"What about the other PR #419 ?",
"Oh this is the PR where I ran make quality and make style and some previous files from master were changed",
"Oh right ! Let me fix the style myself if you don't mind"
] | 1,595,275,709,000 | 1,595,434,120,000 | 1,595,434,119,000 | CONTRIBUTOR | null | {
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} | Changes:
- added arrow schema to features conversion (it's going to be useful to fix #342 )
- make flatten handle deep features (useful for tfrecords conversion in #339 )
- add tests for flatten and features conversions
- the reader now returns the kwargs to instantiate a Dataset (fix circular dependencies) | https://api.github.com/repos/huggingface/datasets/issues/420/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/419 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/419/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/419/comments | https://api.github.com/repos/huggingface/datasets/issues/419/events | https://github.com/huggingface/datasets/pull/419 | 661,974,747 | MDExOlB1bGxSZXF1ZXN0NDUzNTgxNzQz | 419 | EmoContext dataset add | {
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Signed-off-by: lordtt13 <thakurtanmay72@yahoo.com> | https://api.github.com/repos/huggingface/datasets/issues/419/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/418 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/418/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/418/comments | https://api.github.com/repos/huggingface/datasets/issues/418/events | https://github.com/huggingface/datasets/issues/418 | 661,914,873 | MDU6SXNzdWU2NjE5MTQ4NzM= | 418 | Addition of google drive links to dl_manager | {
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"I think the problem is the way you wrote your urls. Try the following structure to see `https://drive.google.com/uc?export=download&id=your_file_id` . \r\n\r\n@lhoestq ",
"Oh sorry, I think `_get_drive_url` is doing that. \r\n\r\nHave you tried to use `dl_manager.download_and_extract(_get_drive_url(_TRAIN_URL)`... | 1,595,256,722,000 | 1,595,259,572,000 | 1,595,259,572,000 | CONTRIBUTOR | null | null | Hello there, I followed the template to create a download script of my own, which works fine for me, although I had to shun the dl_manager because it was downloading nothing from the drive links and instead use gdown.
This is the script for me:
```python
class EmoConfig(nlp.BuilderConfig):
"""BuilderConfig ... | https://api.github.com/repos/huggingface/datasets/issues/418/timeline | null | false |
https://api.github.com/repos/huggingface/datasets/issues/417 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/417/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/417/comments | https://api.github.com/repos/huggingface/datasets/issues/417/events | https://github.com/huggingface/datasets/pull/417 | 661,804,054 | MDExOlB1bGxSZXF1ZXN0NDUzNDMyODE5 | 417 | Fix docstrins multiple metrics instances | {
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} | We change the docstrings of `nlp.Metric.compute`, `nlp.Metric.add` and `nlp.Metric.add_batch` depending on which metric is instantiated. However we had issues when instantiating multiple metrics (docstrings were duplicated).
This should fix #304 | https://api.github.com/repos/huggingface/datasets/issues/417/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/416 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/416/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/416/comments | https://api.github.com/repos/huggingface/datasets/issues/416/events | https://github.com/huggingface/datasets/pull/416 | 661,635,393 | MDExOlB1bGxSZXF1ZXN0NDUzMjg1NTM4 | 416 | Fix xtreme panx directory | {
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"great, I think I did not download the data the way you do, but yours is more reasonable."
] | 1,595,239,757,000 | 1,595,319,346,000 | 1,595,319,344,000 | MEMBER | null | {
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https://api.github.com/repos/huggingface/datasets/issues/415 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/415/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/415/comments | https://api.github.com/repos/huggingface/datasets/issues/415/events | https://github.com/huggingface/datasets/issues/415 | 660,687,076 | MDU6SXNzdWU2NjA2ODcwNzY= | 415 | Something is wrong with WMT 19 kk-en dataset | {
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```
>>>import nlp
>>>from nlp import load_dataset
>>>dataset = load_dataset('wmt19', 'kk-en')
>>>dataset["train"]["translation"][0]
{'kk': 'Trumpian Uncertainty', 'en': 'Трамптық белгісіздік'}
>>>dataset["validation"]["translation"][0]
{'kk': 'Ақша-несие... | https://api.github.com/repos/huggingface/datasets/issues/415/timeline | null | false |
https://api.github.com/repos/huggingface/datasets/issues/414 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/414/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/414/comments | https://api.github.com/repos/huggingface/datasets/issues/414/events | https://github.com/huggingface/datasets/issues/414 | 660,654,013 | MDU6SXNzdWU2NjA2NTQwMTM= | 414 | from_dict delete? | {
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"`from_dict` was added in #350 that was unfortunately not included in the 0.3.0 release. It's going to be included in the next release that will be out pretty soon though.\r\nRight now if you want to use `from_dict` you have to install the package from the master branch\r\n```\r\npip install git+https://github.com/... | 1,595,142,516,000 | 1,595,298,077,000 | 1,595,298,077,000 | NONE | null | null | AttributeError: type object 'Dataset' has no attribute 'from_dict' | https://api.github.com/repos/huggingface/datasets/issues/414/timeline | null | false |
https://api.github.com/repos/huggingface/datasets/issues/413 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/413/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/413/comments | https://api.github.com/repos/huggingface/datasets/issues/413/events | https://github.com/huggingface/datasets/issues/413 | 660,063,655 | MDU6SXNzdWU2NjAwNjM2NTU= | 413 | Is there a way to download only NQ dev? | {
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"Unfortunately it's not possible to download only the dev set of NQ.\r\n\r\nI think we could add a way to download only the test set by adding a custom configuration to the processing script though.",
"Ok, got it. I think this could be a valuable feature - especially for large datasets like NQ, but potentially al... | 1,595,068,103,000 | 1,596,027,980,000 | null | NONE | null | null | Maybe I missed that in the docs, but is there a way to only download the dev set of natural questions (~1 GB)?
As we want to benchmark QA models on different datasets, I would like to avoid downloading the 41GB of training data.
I tried
```
dataset = nlp.load_dataset('natural_questions', split="validation", bea... | https://api.github.com/repos/huggingface/datasets/issues/413/timeline | null | false |
https://api.github.com/repos/huggingface/datasets/issues/412 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/412/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/412/comments | https://api.github.com/repos/huggingface/datasets/issues/412/events | https://github.com/huggingface/datasets/issues/412 | 660,047,139 | MDU6SXNzdWU2NjAwNDcxMzk= | 412 | Unable to load XTREME dataset from disk | {
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"Hi @lewtun, you have to provide the full path to the downloaded file for example `/home/lewtum/..`",
"I was able to repro. Opening a PR to fix that.\r\nThanks for reporting this issue !",
"Thanks for the rapid fix @lhoestq!"
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## Description of the problem
Following the [docs](https://huggingface.co/nlp/loading_datasets.html?highlight=xtreme#manually-downloading-files) I'm trying to load the `PAN-X.fr` dataset from the [XTREME](https://github.com/google-research/xtreme) benchmark.
I have manually downloaded the `AmazonPho... | https://api.github.com/repos/huggingface/datasets/issues/412/timeline | null | false |
https://api.github.com/repos/huggingface/datasets/issues/411 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/411/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/411/comments | https://api.github.com/repos/huggingface/datasets/issues/411/events | https://github.com/huggingface/datasets/pull/411 | 659,393,398 | MDExOlB1bGxSZXF1ZXN0NDUxMjQxOTQy | 411 | Sbf | {
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dataset homepage: https://homes.cs.washington.edu/~msap/social-bias-frames/ | https://api.github.com/repos/huggingface/datasets/issues/411/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/410 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/410/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/410/comments | https://api.github.com/repos/huggingface/datasets/issues/410/events | https://github.com/huggingface/datasets/pull/410 | 659,242,871 | MDExOlB1bGxSZXF1ZXN0NDUxMTEzMTI3 | 410 | 20newsgroup | {
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#353 | https://api.github.com/repos/huggingface/datasets/issues/410/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/409 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/409/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/409/comments | https://api.github.com/repos/huggingface/datasets/issues/409/events | https://github.com/huggingface/datasets/issues/409 | 659,128,611 | MDU6SXNzdWU2NTkxMjg2MTE= | 409 | train_test_split error: 'dict' object has no attribute 'deepcopy' | {
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"It was fixed in 2ddd18d139d3047c9c3abe96e1e7d05bb360132c.\r\nCould you pull the latest changes from master @morganmcg1 ?",
"Thanks @lhoestq, works fine now!"
] | 1,594,982,188,000 | 1,595,342,092,000 | 1,595,342,092,000 | NONE | null | null | `train_test_split` is giving me an error when I try and call it:
`'dict' object has no attribute 'deepcopy'`
## To reproduce
```
dataset = load_dataset('glue', 'mrpc', split='train')
dataset = dataset.train_test_split(test_size=0.2)
```
## Full Stacktrace
```
-------------------------------------------... | https://api.github.com/repos/huggingface/datasets/issues/409/timeline | null | false |
https://api.github.com/repos/huggingface/datasets/issues/408 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/408/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/408/comments | https://api.github.com/repos/huggingface/datasets/issues/408/events | https://github.com/huggingface/datasets/pull/408 | 659,064,144 | MDExOlB1bGxSZXF1ZXN0NDUwOTU1MTE0 | 408 | Add tests datasets gcp | {
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} | Some datasets are available on our google cloud storage in arrow format, so that the users don't need to process the data.
These tests make sure that they're always available. It also makes sure that their scripts are in sync between S3 and the repo.
This should avoid future issues like #407 | https://api.github.com/repos/huggingface/datasets/issues/408/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/407 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/407/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/407/comments | https://api.github.com/repos/huggingface/datasets/issues/407/events | https://github.com/huggingface/datasets/issues/407 | 658,672,736 | MDU6SXNzdWU2NTg2NzI3MzY= | 407 | MissingBeamOptions for Wikipedia 20200501.en | {
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"Fixed. Could you try again @mitchellgordon95 ?\r\nIt was due a file not being updated on S3.\r\n\r\nWe need to make sure all the datasets scripts get updated properly @julien-c ",
"Works for me! Thanks.",
"I found the same issue with almost any language other than English. (For English, it works). Will someone... | 1,594,943,283,000 | 1,610,451,676,000 | 1,594,995,868,000 | CONTRIBUTOR | null | null | There may or may not be a regression for the pre-processed Wikipedia dataset. This was working fine 10 commits ago (without having Apache Beam available):
```
nlp.load_dataset('wikipedia', "20200501.en", split='train')
```
And now, having pulled master, I get:
```
Downloading and preparing dataset wikipedia... | https://api.github.com/repos/huggingface/datasets/issues/407/timeline | null | false |
https://api.github.com/repos/huggingface/datasets/issues/406 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/406/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/406/comments | https://api.github.com/repos/huggingface/datasets/issues/406/events | https://github.com/huggingface/datasets/issues/406 | 658,581,764 | MDU6SXNzdWU2NTg1ODE3NjQ= | 406 | Faster Shuffling? | {
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"I think the slowness here probably come from the fact that we are copying from and to python.\r\n\r\n@lhoestq for all the `select`-based methods I think we should stay in Arrow format and update the writer so that it can accept Arrow tables or batches as well. What do you think?",
"> @lhoestq for all the `select... | 1,594,934,513,000 | 1,599,489,926,000 | 1,599,489,925,000 | CONTRIBUTOR | null | null | Consider shuffling bookcorpus:
```
dataset = nlp.load_dataset('bookcorpus', split='train')
dataset.shuffle()
```
According to tqdm, this will take around 2.5 hours on my machine to complete (even with the faster version of select from #405). I've also tried with `keep_in_memory=True` and `writer_batch_size=1000`... | https://api.github.com/repos/huggingface/datasets/issues/406/timeline | null | false |
https://api.github.com/repos/huggingface/datasets/issues/405 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/405/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/405/comments | https://api.github.com/repos/huggingface/datasets/issues/405/events | https://github.com/huggingface/datasets/pull/405 | 658,580,192 | MDExOlB1bGxSZXF1ZXN0NDUwNTI1MTc3 | 405 | Make select() faster by batching reads | {
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} | Here's a benchmark:
```
dataset = nlp.load_dataset('bookcorpus', split='train')
start = time.time()
dataset.select(np.arange(1000), reader_batch_size=1, load_from_cache_file=False)
end = time.time()
print(f'{end - start}')
start = time.time()
dataset.select(np.arange(1000), reader_batch_size=1000, load_fr... | https://api.github.com/repos/huggingface/datasets/issues/405/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/404 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/404/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/404/comments | https://api.github.com/repos/huggingface/datasets/issues/404/events | https://github.com/huggingface/datasets/pull/404 | 658,400,987 | MDExOlB1bGxSZXF1ZXN0NDUwMzY4Mjg4 | 404 | Add seed in metrics | {
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} | With #361 we noticed that some metrics were not deterministic.
In this PR I allow the user to specify numpy's seed when instantiating a metric with `load_metric`.
The seed is set only when `compute` is called, and reset afterwards.
Moreover when calling `compute` with the same metric instance (i.e. same experiment... | https://api.github.com/repos/huggingface/datasets/issues/404/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/403 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/403/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/403/comments | https://api.github.com/repos/huggingface/datasets/issues/403/events | https://github.com/huggingface/datasets/pull/403 | 658,325,756 | MDExOlB1bGxSZXF1ZXN0NDUwMzAzNjI2 | 403 | return python objects instead of arrays by default | {
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} | We were using to_pandas() to convert from arrow types, however it returns numpy arrays instead of python lists.
I fixed it by using to_pydict/to_pylist instead.
Fix #387
It was mentioned in https://github.com/huggingface/transformers/issues/5729
| https://api.github.com/repos/huggingface/datasets/issues/403/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/402 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/402/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/402/comments | https://api.github.com/repos/huggingface/datasets/issues/402/events | https://github.com/huggingface/datasets/pull/402 | 658,001,288 | MDExOlB1bGxSZXF1ZXN0NDUwMDI2NTE0 | 402 | Search qa | {
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} | add SearchQA dataset
#336 | https://api.github.com/repos/huggingface/datasets/issues/402/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/401 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/401/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/401/comments | https://api.github.com/repos/huggingface/datasets/issues/401/events | https://github.com/huggingface/datasets/pull/401 | 657,996,252 | MDExOlB1bGxSZXF1ZXN0NDUwMDIyNTc0 | 401 | add web_questions | {
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"What does the `nlp-cli dummy_data` command returns ?",
"`test.json` -> `test` \r\nand \r\n`train.json` -> `train`\r\n\r\nas shown by the `nlp-cli dummy_data` command ;-)",
"LGTM for merge @lhoestq - I let you merge if you want to."
] | 1,594,889,699,000 | 1,596,694,580,000 | 1,596,694,579,000 | CONTRIBUTOR | null | {
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#336
Maybe @patrickvonplaten you can help with the dummy_data structure? it still broken | https://api.github.com/repos/huggingface/datasets/issues/401/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/400 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/400/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/400/comments | https://api.github.com/repos/huggingface/datasets/issues/400/events | https://github.com/huggingface/datasets/pull/400 | 657,975,600 | MDExOlB1bGxSZXF1ZXN0NDUwMDA1MDU5 | 400 | Web questions | {
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#336 | https://api.github.com/repos/huggingface/datasets/issues/400/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/399 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/399/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/399/comments | https://api.github.com/repos/huggingface/datasets/issues/399/events | https://github.com/huggingface/datasets/pull/399 | 657,841,433 | MDExOlB1bGxSZXF1ZXN0NDQ5ODkxNTEy | 399 | Spelling mistake | {
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"Thanks!"
] | 1,594,874,278,000 | 1,594,882,188,000 | 1,594,882,177,000 | CONTRIBUTOR | null | {
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} | In "Formatting the dataset" part, "The two toehr modifications..." should be "The two other modifications..." ,the word "other" wrong spelled as "toehr". | https://api.github.com/repos/huggingface/datasets/issues/399/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/398 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/398/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/398/comments | https://api.github.com/repos/huggingface/datasets/issues/398/events | https://github.com/huggingface/datasets/pull/398 | 657,511,962 | MDExOlB1bGxSZXF1ZXN0NDQ5NjE1OTk1 | 398 | Add inline links | {
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"Do you mind adding a link to the much more extended pages on adding and sharing a dataset in the new documentation?",
"Sure, I will do that too"
] | 1,594,832,644,000 | 1,595,412,862,000 | 1,595,412,862,000 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/datasets/issues/397 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/397/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/397/comments | https://api.github.com/repos/huggingface/datasets/issues/397/events | https://github.com/huggingface/datasets/pull/397 | 657,510,856 | MDExOlB1bGxSZXF1ZXN0NDQ5NjE1MDA4 | 397 | Add contiguous sharding | {
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} | This makes dset.shard() play nice with nlp.concatenate_datasets(). When I originally wrote the shard() method, I was thinking about a distributed training scenario, but https://github.com/huggingface/nlp/pull/389 also uses it for splitting the dataset for distributed preprocessing.
Usage:
```
nlp.concatenate_datas... | https://api.github.com/repos/huggingface/datasets/issues/397/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/396 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/396/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/396/comments | https://api.github.com/repos/huggingface/datasets/issues/396/events | https://github.com/huggingface/datasets/pull/396 | 657,477,952 | MDExOlB1bGxSZXF1ZXN0NDQ5NTg3MDQ4 | 396 | Fix memory issue when doing select | {
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} | We were passing the `nlp.Dataset` object to get the hash for the new dataset's file name.
Fix #395 | https://api.github.com/repos/huggingface/datasets/issues/396/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/395 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/395/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/395/comments | https://api.github.com/repos/huggingface/datasets/issues/395/events | https://github.com/huggingface/datasets/issues/395 | 657,454,983 | MDU6SXNzdWU2NTc0NTQ5ODM= | 395 | Memory issue when doing select | {
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```python
import nlp
w = nlp.load_dataset("wikipedia", "20200501.en", split="train")
w.select([0])
```
This is caused by [this line](https://github.com/huggingface/nlp/blob/master/src/nlp/arrow_dataset.py#L626) for some reason, that ... | https://api.github.com/repos/huggingface/datasets/issues/395/timeline | null | false |
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#378 | https://api.github.com/repos/huggingface/datasets/issues/394/timeline | null | true |
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} | The cache dir was often cluttered by extracted files because of the download manager.
For downloaded files, we are using the `downloads` directory to make things easier to navigate, but extracted files were still placed at the root of the cache directory. To fix that I changed the directory for extracted files to ca... | https://api.github.com/repos/huggingface/datasets/issues/393/timeline | null | true |
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} | Another [PAN task](https://pan.webis.de/clef20/pan20-web/style-change-detection.html). This time about identifying when the style/author changes in documents.
- There's the possibility of adding the [PAN19](https://zenodo.org/record/3577602) and PAN18 style change detection tasks too (these are datasets whose labels... | https://api.github.com/repos/huggingface/datasets/issues/392/timeline | null | true |
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Abstract :
>Models that surpass human performance on several popular benchmarks display significant degradation in performance on exposure to Out of Distribution (OOD) data. Recent research has shown that models overfit to spurious biases and ‘hack’ datasets... | https://api.github.com/repos/huggingface/datasets/issues/391/timeline | null | false |
https://api.github.com/repos/huggingface/datasets/issues/390 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/390/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/390/comments | https://api.github.com/repos/huggingface/datasets/issues/390/events | https://github.com/huggingface/datasets/pull/390 | 656,956,384 | MDExOlB1bGxSZXF1ZXN0NDQ5MTYxMzY3 | 390 | Concatenate datasets | {
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"Looks cool :)\r\n\r\nI feel like \r\n```python\r\nconcatenated_dataset = dataset1.concatenate(dataset2)\r\n```\r\ncould be more natural. What do you think ?\r\n\r\nAlso could you also concatenate the `nlp.Dataset._data_files` ?\r\n```python\r\nreturn cls(table, info=info, split=split, data_files=self._data_files +... | 1,594,769,077,000 | 1,595,411,398,000 | 1,595,411,398,000 | CONTRIBUTOR | null | {
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} | I'm constructing the "WikiBooks" dataset, which is a concatenation of Wikipedia & BookCorpus. So I implemented the `Dataset.from_concat()` method, which concatenates two datasets with the same schema.
This would also be useful if someone wants to pretrain on a large generic dataset + their own custom dataset. Not in... | https://api.github.com/repos/huggingface/datasets/issues/390/timeline | null | true |
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"By the way, the reason this is an issue for me is because I want to be able to \"save\" changes made to a dataset by writing something to disk. In this case, I would like to pre-process my dataset once, and then train multiple models on the dataset later without having to re-process the data. \r\n\r\nIs pickling/u... | 1,594,763,619,000 | 1,596,551,890,000 | 1,596,551,890,000 | CONTRIBUTOR | null | {
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} | It would be nice to pickle and unpickle Datasets, as done in [this tutorial](https://github.com/patil-suraj/exploring-T5/blob/master/T5_on_TPU.ipynb). Example:
```
wiki = nlp.load_dataset('wikipedia', split='train')
def sentencize(examples):
...
wiki = wiki.map(sentencize, batched=True)
torch.save(wiki, '... | https://api.github.com/repos/huggingface/datasets/issues/389/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/388 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/388/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/388/comments | https://api.github.com/repos/huggingface/datasets/issues/388/events | https://github.com/huggingface/datasets/issues/388 | 656,707,497 | MDU6SXNzdWU2NTY3MDc0OTc= | 388 | 🐛 [Dataset] Cannot download wmt14, wmt15 and wmt17 | {
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"similar slow download speed here for nlp.load_dataset('wmt14', 'fr-en')\r\n`\r\nDownloading: 100%|██████████████████████████████████████████████████████████| 658M/658M [1:00:42<00:00, 181kB/s]\r\nDownloading: 100%|██████████████████████████████████████████████████████████| 918M/918M [1:39:38<00:00, 154kB/s]\r\nDow... | 1,594,741,001,000 | 1,596,639,392,000 | null | NONE | null | null | 1. I try downloading `wmt14`, `wmt15`, `wmt17`, `wmt19` with the following code:
```
nlp.load_dataset('wmt14','de-en')
nlp.load_dataset('wmt15','de-en')
nlp.load_dataset('wmt17','de-en')
nlp.load_dataset('wmt19','de-en')
```
The code runs but the download speed is **extremely slow**, the same behaviour is not ob... | https://api.github.com/repos/huggingface/datasets/issues/388/timeline | null | false |
https://api.github.com/repos/huggingface/datasets/issues/387 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/387/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/387/comments | https://api.github.com/repos/huggingface/datasets/issues/387/events | https://github.com/huggingface/datasets/issues/387 | 656,361,357 | MDU6SXNzdWU2NTYzNjEzNTc= | 387 | Conversion through to_pandas output numpy arrays for lists instead of python objects | {
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"To convert from arrow type we have three options: to_numpy, to_pandas and to_pydict/to_pylist.\r\n\r\n- to_numpy and to_pandas return numpy arrays instead of lists but are very fast.\r\n- to_pydict/to_pylist can be 100x slower and become the bottleneck for reading data, but at least they return lists.\r\n\r\nMaybe... | 1,594,707,841,000 | 1,594,985,820,000 | 1,594,985,820,000 | MEMBER | null | null | In a related question, the conversion through to_pandas output numpy arrays for the lists instead of python objects.
Here is an example:
```python
>>> dataset._data.slice(key, 1).to_pandas().to_dict("list")
{'sentence1': ['Amrozi accused his brother , whom he called " the witness " , of deliberately distorting hi... | https://api.github.com/repos/huggingface/datasets/issues/387/timeline | null | false |
https://api.github.com/repos/huggingface/datasets/issues/386 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/386/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/386/comments | https://api.github.com/repos/huggingface/datasets/issues/386/events | https://github.com/huggingface/datasets/pull/386 | 655,839,067 | MDExOlB1bGxSZXF1ZXN0NDQ4MjQ1NDI4 | 386 | Update dataset loading and features - Add TREC dataset | {
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"I just copied the files that are on google storage to follow the new `_relative_data_dir ` format. It should be good to merge now :)\r\n\r\nWell actually it seems there are some merge conflicts to fix first"
] | 1,594,645,818,000 | 1,594,887,478,000 | 1,594,887,478,000 | MEMBER | null | {
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} | This PR:
- add a template for a new dataset script
- update the caching structure so that the path to the cached data files is also a function of the dataset loading script hash. This way when you update a loading script the data will be automatically updated instead of falling back to the previous version (which is ... | https://api.github.com/repos/huggingface/datasets/issues/386/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/385 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/385/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/385/comments | https://api.github.com/repos/huggingface/datasets/issues/385/events | https://github.com/huggingface/datasets/pull/385 | 655,663,997 | MDExOlB1bGxSZXF1ZXN0NDQ4MTAzMjY5 | 385 | Remove unnecessary nested dict | {
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"We can probably scan the dataset scripts with a regexpr to try to identify this pattern cc @patrickvonplaten maybe",
"@mariamabarham This script should work. I tested it for a couple of datasets. There might be exceptions where the script breaks - did not test everything.\r\n\r\n```python\r\n#!/usr/bin/env pytho... | 1,594,629,983,000 | 1,594,812,458,000 | 1,594,807,433,000 | CONTRIBUTOR | null | {
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} | This PR is removing unnecessary nested dictionary used in some datasets. For now the following datasets are updated:
- MLQA
- RACE
Will be adding more if necessary.
#378 | https://api.github.com/repos/huggingface/datasets/issues/385/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/383 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/383/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/383/comments | https://api.github.com/repos/huggingface/datasets/issues/383/events | https://github.com/huggingface/datasets/pull/383 | 655,291,201 | MDExOlB1bGxSZXF1ZXN0NDQ3ODI0OTky | 383 | Adding the Linguistic Code-switching Evaluation (LinCE) benchmark | {
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"I am checking the details of the CI log for the failed test, but I don't see how the error relates to the code I added; the error is coming from a config builder different than the `LinceConfig`, and it crashes when `self.config.data_files` because is self.config is None. I would appreciate if someone could help m... | 1,594,506,920,000 | 1,594,916,386,000 | 1,594,916,386,000 | CONTRIBUTOR | null | {
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} | Hi,
First of all, this library is really cool! Thanks for putting all of this together!
This PR contains the [Linguistic Code-switching Evaluation (LinCE) benchmark](https://ritual.uh.edu/lince). As described in the official website (FAQ):
> 1. Why do we need LinCE?
>LinCE brings 10 code-switching datasets t... | https://api.github.com/repos/huggingface/datasets/issues/383/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/382 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/382/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/382/comments | https://api.github.com/repos/huggingface/datasets/issues/382/events | https://github.com/huggingface/datasets/issues/382 | 655,290,482 | MDU6SXNzdWU2NTUyOTA0ODI= | 382 | 1080 | {
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https://api.github.com/repos/huggingface/datasets/issues/381 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/381/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/381/comments | https://api.github.com/repos/huggingface/datasets/issues/381/events | https://github.com/huggingface/datasets/issues/381 | 655,277,119 | MDU6SXNzdWU2NTUyNzcxMTk= | 381 | NLp | {
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https://api.github.com/repos/huggingface/datasets/issues/378 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/378/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/378/comments | https://api.github.com/repos/huggingface/datasets/issues/378/events | https://github.com/huggingface/datasets/issues/378 | 655,226,316 | MDU6SXNzdWU2NTUyMjYzMTY= | 378 | [dataset] Structure of MLQA seems unecessary nested | {
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"Same for the RACE dataset: https://github.com/huggingface/nlp/blob/master/datasets/race/race.py\r\n\r\nShould we scan all the datasets to remove this pattern of un-necessary nesting?",
"You're right, I think we don't need to use the nested dictionary. \r\n"
] | 1,594,480,568,000 | 1,594,829,840,000 | 1,594,829,840,000 | MEMBER | null | null | The features of the MLQA dataset comprise several nested dictionaries with a single element inside (for `questions` and `ids`): https://github.com/huggingface/nlp/blob/master/datasets/mlqa/mlqa.py#L90-L97
Should we keep this @mariamabarham @patrickvonplaten? Was this added for compatibility with tfds?
```python
... | https://api.github.com/repos/huggingface/datasets/issues/378/timeline | null | false |
https://api.github.com/repos/huggingface/datasets/issues/377 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/377/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/377/comments | https://api.github.com/repos/huggingface/datasets/issues/377/events | https://github.com/huggingface/datasets/issues/377 | 655,215,790 | MDU6SXNzdWU2NTUyMTU3OTA= | 377 | Iyy!!! | {
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https://api.github.com/repos/huggingface/datasets/issues/376 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/376/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/376/comments | https://api.github.com/repos/huggingface/datasets/issues/376/events | https://github.com/huggingface/datasets/issues/376 | 655,047,826 | MDU6SXNzdWU2NTUwNDc4MjY= | 376 | to_pandas conversion doesn't always work | {
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"**Edit**: other topic previously in this message moved to a new issue: https://github.com/huggingface/nlp/issues/387",
"Could you try to update pyarrow to >=0.17.0 ? It should fix the `to_pandas` bug\r\n\r\nAlso I'm not sure that structures like list<struct> are fully supported in the lib (none of the datasets u... | 1,594,416,811,000 | 1,595,239,845,000 | null | MEMBER | null | null | For some complex nested types, the conversion from Arrow to python dict through pandas doesn't seem to be possible.
Here is an example using the official SQUAD v2 JSON file.
This example was found while investigating #373.
```python
>>> squad = load_dataset('json', data_files={nlp.Split.TRAIN: ["./train-v2.0.... | https://api.github.com/repos/huggingface/datasets/issues/376/timeline | null | false |
https://api.github.com/repos/huggingface/datasets/issues/375 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/375/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/375/comments | https://api.github.com/repos/huggingface/datasets/issues/375/events | https://github.com/huggingface/datasets/issues/375 | 655,023,307 | MDU6SXNzdWU2NTUwMjMzMDc= | 375 | TypeError when computing bertscore | {
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"I am not able to reproduce this issue on my side.\r\nCould you give us more details about the inputs you used ?\r\n\r\nI do get another error though:\r\n```\r\n~/.virtualenvs/hf-datasets/lib/python3.7/site-packages/bert_score/utils.py in bert_cos_score_idf(model, refs, hyps, tokenizer, idf_dict, verbose, batch_siz... | 1,594,413,464,000 | 1,599,490,212,000 | null | NONE | null | null | Hi,
I installed nlp 0.3.0 via pip, and my python version is 3.7.
When I tried to compute bertscore with the code:
```
import nlp
bertscore = nlp.load_metric('bertscore')
# load hyps and refs
...
print (bertscore.compute(hyps, refs, lang='en'))
```
I got the following error.
```
Traceback (most rece... | https://api.github.com/repos/huggingface/datasets/issues/375/timeline | null | false |
https://api.github.com/repos/huggingface/datasets/issues/374 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/374/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/374/comments | https://api.github.com/repos/huggingface/datasets/issues/374/events | https://github.com/huggingface/datasets/pull/374 | 654,895,066 | MDExOlB1bGxSZXF1ZXN0NDQ3NTMxMzUy | 374 | Add dataset post processing for faiss indexes | {
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"I changed the `wiki_dpr` script to ignore the last 24 examples for now. Hopefully we'll have the full version soon.\r\nThe datasets_infos.json and the data on GCS are updated.\r\n\r\nAnd I also added a check to make sure we don't have post processing resources in sub-directories.",
"I added a dummy config that c... | 1,594,398,359,000 | 1,594,647,843,000 | 1,594,647,841,000 | MEMBER | null | {
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} | # Post processing of datasets for faiss indexes
Now that we can have datasets with embeddings (see `wiki_pr` for example), we can allow users to load the dataset + get the Faiss index that comes with it to do nearest neighbors queries.
## Implementation proposition
- Faiss indexes have to be added to the `nlp.... | https://api.github.com/repos/huggingface/datasets/issues/374/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/373 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/373/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/373/comments | https://api.github.com/repos/huggingface/datasets/issues/373/events | https://github.com/huggingface/datasets/issues/373 | 654,845,133 | MDU6SXNzdWU2NTQ4NDUxMzM= | 373 | Segmentation fault when loading local JSON dataset as of #372 | {
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"I've seen this sort of thing before -- it might help to delete the directory -- I've also noticed that there is an error with the json Dataloader for any data I've tried to load. I've replaced it with this, which skips over the data feature population step:\r\n\r\n\r\n```python\r\nimport os\r\n\r\nimport pyarrow.j... | 1,594,393,465,000 | 1,608,017,240,000 | null | CONTRIBUTOR | null | null | The last issue was closed (#369) once the #372 update was merged. However, I'm still not able to load a SQuAD formatted JSON file. Instead of the previously recorded pyarrow error, I now get a segmentation fault.
```
dataset = nlp.load_dataset('json', data_files={nlp.Split.TRAIN: ["./datasets/train-v2.0.json"]}, f... | https://api.github.com/repos/huggingface/datasets/issues/373/timeline | null | false |
https://api.github.com/repos/huggingface/datasets/issues/372 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/372/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/372/comments | https://api.github.com/repos/huggingface/datasets/issues/372/events | https://github.com/huggingface/datasets/pull/372 | 654,774,420 | MDExOlB1bGxSZXF1ZXN0NDQ3NDMzNTA4 | 372 | Make the json script more flexible | {
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} | Fix https://github.com/huggingface/nlp/issues/359
Fix https://github.com/huggingface/nlp/issues/369
JSON script now can accept JSON files containing a single dict with the records as a list in one attribute to the dict (previously it only accepted JSON files containing records as rows of dicts in the file).
In t... | https://api.github.com/repos/huggingface/datasets/issues/372/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/371 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/371/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/371/comments | https://api.github.com/repos/huggingface/datasets/issues/371/events | https://github.com/huggingface/datasets/pull/371 | 654,668,242 | MDExOlB1bGxSZXF1ZXN0NDQ3MzQ4NDgw | 371 | Fix cached file path for metrics with different config names | {
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"Thanks for the fast fix!"
] | 1,594,375,344,000 | 1,594,388,722,000 | 1,594,388,720,000 | MEMBER | null | {
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It should fix #368 | https://api.github.com/repos/huggingface/datasets/issues/371/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/370 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/370/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/370/comments | https://api.github.com/repos/huggingface/datasets/issues/370/events | https://github.com/huggingface/datasets/pull/370 | 654,304,193 | MDExOlB1bGxSZXF1ZXN0NDQ3MDU3NTIw | 370 | Allow indexing Dataset via np.ndarray | {
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"Looks like a flaky CI, failed download from S3."
] | 1,594,323,795,000 | 1,594,389,944,000 | 1,594,389,943,000 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/datasets/issues/369 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/369/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/369/comments | https://api.github.com/repos/huggingface/datasets/issues/369/events | https://github.com/huggingface/datasets/issues/369 | 654,186,890 | MDU6SXNzdWU2NTQxODY4OTA= | 369 | can't load local dataset: pyarrow.lib.ArrowInvalid: straddling object straddles two block boundaries | {
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"I am able to reproduce this with the official SQuAD `train-v2.0.json` file downloaded directly from https://rajpurkar.github.io/SQuAD-explorer/",
"I am facing this issue in transformers library 3.0.2 while reading a csv using datasets.\r\nIs this fixed in latest version? \r\nI updated the latest version 4.0.1 bu... | 1,594,311,413,000 | 1,608,073,642,000 | 1,594,392,726,000 | CONTRIBUTOR | null | null | Trying to load a local SQuAD-formatted dataset (from a JSON file, about 60MB):
```
dataset = nlp.load_dataset(path='json', data_files={nlp.Split.TRAIN: ["./path/to/file.json"]})
```
causes
```
Traceback (most recent call last):
File "dataloader.py", line 9, in <module>
["./path/to/file.json"]})
File "/... | https://api.github.com/repos/huggingface/datasets/issues/369/timeline | null | false |
https://api.github.com/repos/huggingface/datasets/issues/368 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/368/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/368/comments | https://api.github.com/repos/huggingface/datasets/issues/368/events | https://github.com/huggingface/datasets/issues/368 | 654,087,251 | MDU6SXNzdWU2NTQwODcyNTE= | 368 | load_metric can't acquire lock anymore | {
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"I found that, in the same process (or the same interactive session), if I do\r\n\r\nimport nlp\r\n\r\nm1 = nlp.load_metric('glue', 'mrpc')\r\nm2 = nlp.load_metric('glue', 'sst2')\r\n\r\nI will get the same error `ValueError: Cannot acquire lock, caching file might be used by another process, you should setup a uni... | 1,594,303,449,000 | 1,594,388,720,000 | 1,594,388,720,000 | NONE | null | null | I can't load metric (glue) anymore after an error in a previous run. I even removed the whole cache folder `/home/XXX/.cache/huggingface/`, and the issue persisted. What are the steps to fix this?
Traceback (most recent call last):
File "/home/XXX/miniconda3/envs/ML-DL-py-3.7/lib/python3.7/site-packages/n... | https://api.github.com/repos/huggingface/datasets/issues/368/timeline | null | false |
https://api.github.com/repos/huggingface/datasets/issues/367 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/367/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/367/comments | https://api.github.com/repos/huggingface/datasets/issues/367/events | https://github.com/huggingface/datasets/pull/367 | 654,012,984 | MDExOlB1bGxSZXF1ZXN0NDQ2ODIxNTAz | 367 | Update Xtreme to add PAWS-X es | {
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} | This PR adds the `PAWS-X.es` in the Xtreme dataset #362 | https://api.github.com/repos/huggingface/datasets/issues/367/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/366 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/366/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/366/comments | https://api.github.com/repos/huggingface/datasets/issues/366/events | https://github.com/huggingface/datasets/pull/366 | 653,954,896 | MDExOlB1bGxSZXF1ZXN0NDQ2NzcyODE2 | 366 | Add quora dataset | {
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"Tests seem to be failing because of pandas",
"Kaggle needs authentification to download datasets. We don't have a way to handle that in the lib for now"
] | 1,594,290,862,000 | 1,594,661,721,000 | 1,594,661,721,000 | CONTRIBUTOR | null | {
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} | Added the [Quora question pairs dataset](https://www.quora.com/q/quoradata/First-Quora-Dataset-Release-Question-Pairs).
Implementation Notes:
- I used the original version provided on the quora website. There's also a [Kaggle competition](https://www.kaggle.com/c/quora-question-pairs) which has a nice train/test sp... | https://api.github.com/repos/huggingface/datasets/issues/366/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/365 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/365/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/365/comments | https://api.github.com/repos/huggingface/datasets/issues/365/events | https://github.com/huggingface/datasets/issues/365 | 653,845,964 | MDU6SXNzdWU2NTM4NDU5NjQ= | 365 | How to augment data ? | {
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"Using batched map is probably the easiest way at the moment.\r\nWhat kind of augmentation would you like to do ?",
"Some samples in the dataset are too long, I want to divide them in several samples.",
"Using batched map is the way to go then.\r\nWe'll make it clearer in the docs that map could be used for aug... | 1,594,281,157,000 | 1,594,372,327,000 | 1,594,369,335,000 | NONE | null | null | Is there any clean way to augment data ?
For now my work-around is to use batched map, like this :
```python
def aug(samples):
# Simply copy the existing data to have x2 amount of data
for k, v in samples.items():
samples[k].extend(v)
return samples
dataset = dataset.map(aug, batched=T... | https://api.github.com/repos/huggingface/datasets/issues/365/timeline | null | false |
https://api.github.com/repos/huggingface/datasets/issues/364 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/364/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/364/comments | https://api.github.com/repos/huggingface/datasets/issues/364/events | https://github.com/huggingface/datasets/pull/364 | 653,821,597 | MDExOlB1bGxSZXF1ZXN0NDQ2NjY0NzM5 | 364 | add MS MARCO dataset | {
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"The dummy data for v2.1 is missing as far as I can see. I think running the dummy data command should work correctly here. ",
"Also, it might be that the structure of the dummy data is wrong - looking at `generate_examples` the structure does not look too easy.",
"The fact that the dummy data for v2.1 is miss... | 1,594,278,679,000 | 1,596,694,549,000 | 1,596,694,548,000 | CONTRIBUTOR | null | {
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} | This PR adds the MS MARCO dataset as requested in this issue #336. MS mARCO has multiple task including:
- Passage and Document Retrieval
- Keyphrase Extraction
- QA and NLG
This PR only adds the 2 versions of the QA and NLG task dataset which was realeased with the original paper here https://arxiv.org/pd... | https://api.github.com/repos/huggingface/datasets/issues/364/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/363 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/363/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/363/comments | https://api.github.com/repos/huggingface/datasets/issues/363/events | https://github.com/huggingface/datasets/pull/363 | 653,821,172 | MDExOlB1bGxSZXF1ZXN0NDQ2NjY0NDIy | 363 | Adding support for generic multi dimensional tensors and auxillary image data for multimodal datasets | {
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"Thank you! I just marked this as a draft PR. It probably would be better to create specific Array2D and Array3D classes as needed instead of a generic MultiArray for now, it should simplify the code a lot too so, I'll update it as such. Also i was meaning to reply earlier, but I wanted to thank you for the testing... | 1,594,278,630,000 | 1,598,263,175,000 | 1,598,263,175,000 | CONTRIBUTOR | null | {
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} | nlp/features.py:
The main factory class is MultiArray, every single time this class is called, a corresponding pyarrow extension array and type class is generated (and added to the list of globals for future use) for a given root data type and set of dimensions/shape. I provide examples on working with this in datas... | https://api.github.com/repos/huggingface/datasets/issues/363/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/362 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/362/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/362/comments | https://api.github.com/repos/huggingface/datasets/issues/362/events | https://github.com/huggingface/datasets/issues/362 | 653,766,245 | MDU6SXNzdWU2NTM3NjYyNDU= | 362 | [dateset subset missing] xtreme paws-x | {
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"You're right, thanks for pointing it out. We will update it "
] | 1,594,271,094,000 | 1,594,298,322,000 | 1,594,298,322,000 | CONTRIBUTOR | null | null | I tried nlp.load_dataset('xtreme', 'PAWS-X.es') but get the value error
It turns out that the subset for Spanish is missing
https://github.com/google-research-datasets/paws/tree/master/pawsx | https://api.github.com/repos/huggingface/datasets/issues/362/timeline | null | false |
https://api.github.com/repos/huggingface/datasets/issues/361 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/361/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/361/comments | https://api.github.com/repos/huggingface/datasets/issues/361/events | https://github.com/huggingface/datasets/issues/361 | 653,757,376 | MDU6SXNzdWU2NTM3NTczNzY= | 361 | 🐛 [Metrics] ROUGE is non-deterministic | {
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"Hi, can you give a full self-contained example to reproduce this behavior?",
"> Hi, can you give a full self-contained example to reproduce this behavior?\r\n\r\nThere is a notebook in the post ;)",
"> If I run the ROUGE metric 2 times, with same predictions / references, the scores are slightly different.\r\n... | 1,594,269,577,000 | 1,595,288,917,000 | 1,595,288,917,000 | NONE | null | null | If I run the ROUGE metric 2 times, with same predictions / references, the scores are slightly different.
Refer to [this Colab notebook](https://colab.research.google.com/drive/1wRssNXgb9ldcp4ulwj-hMJn0ywhDOiDy?usp=sharing) for reproducing the problem.
Example of F-score for ROUGE-1, ROUGE-2, ROUGE-L in 2 differe... | https://api.github.com/repos/huggingface/datasets/issues/361/timeline | null | false |
https://api.github.com/repos/huggingface/datasets/issues/360 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/360/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/360/comments | https://api.github.com/repos/huggingface/datasets/issues/360/events | https://github.com/huggingface/datasets/issues/360 | 653,687,176 | MDU6SXNzdWU2NTM2ODcxNzY= | 360 | [Feature request] Add dataset.ragged_map() function for many-to-many transformations | {
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"Actually `map(batched=True)` can already change the size of the dataset.\r\nIt can accept examples of length `N` and returns a batch of length `M` (can be null or greater than `N`).\r\n\r\nI'll make that explicit in the doc that I'm currently writing.",
"You're two steps ahead of me :) In my testing, it also wor... | 1,594,256,683,000 | 1,594,323,111,000 | 1,594,323,111,000 | CONTRIBUTOR | null | null | `dataset.map()` enables one-to-one transformations. Input one example and output one example. This is helpful for tokenizing and cleaning individual lines.
`dataset.filter()` enables one-to-(one-or-none) transformations. Input one example and output either zero/one example. This is helpful for removing portions from t... | https://api.github.com/repos/huggingface/datasets/issues/360/timeline | null | false |
https://api.github.com/repos/huggingface/datasets/issues/359 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/359/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/359/comments | https://api.github.com/repos/huggingface/datasets/issues/359/events | https://github.com/huggingface/datasets/issues/359 | 653,656,279 | MDU6SXNzdWU2NTM2NTYyNzk= | 359 | ArrowBasedBuilder _prepare_split parse_schema breaks on nested structures | {
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"Hi, it depends on what it is in your `dataset_builder.py` file. Can you share it?\r\n\r\nIf you are just loading `json` files, you can also directly use the `json` script (which will find the schema/features from your JSON structure):\r\n\r\n```python\r\nfrom nlp import load_dataset\r\nds = load_dataset(\"json\", ... | 1,594,250,645,000 | 1,594,392,726,000 | 1,594,392,726,000 | NONE | null | null | I tried using the Json dataloader to load some JSON lines files. but get an exception in the parse_schema function.
```
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-23-9aecfbee53bd> in <mo... | https://api.github.com/repos/huggingface/datasets/issues/359/timeline | null | false |
https://api.github.com/repos/huggingface/datasets/issues/358 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/358/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/358/comments | https://api.github.com/repos/huggingface/datasets/issues/358/events | https://github.com/huggingface/datasets/pull/358 | 653,645,121 | MDExOlB1bGxSZXF1ZXN0NDQ2NTI0NjQ5 | 358 | Starting to add some real doc | {
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"Ok this is starting to be really big so it's probably good to merge this first version of the doc and continue in another PR :)\r\n\r\nThis first version of the doc can be explored here: https://2219-250213286-gh.circle-artifacts.com/0/docs/_build/html/index.html"
] | 1,594,248,783,000 | 1,594,720,697,000 | 1,594,720,695,000 | MEMBER | null | {
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} | Adding a lot of documentation for:
- load a dataset
- explore the dataset object
- process data with the dataset
- add a new dataset script
- share a dataset script
- full package reference
This version of the doc can be explored here: https://2219-250213286-gh.circle-artifacts.com/0/docs/_build/html/index.htm... | https://api.github.com/repos/huggingface/datasets/issues/358/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/357 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/357/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/357/comments | https://api.github.com/repos/huggingface/datasets/issues/357/events | https://github.com/huggingface/datasets/pull/357 | 653,642,292 | MDExOlB1bGxSZXF1ZXN0NDQ2NTIyMzU2 | 357 | Add hashes to cnn_dailymail | {
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"Looks you to me :)\r\n\r\nCould you also update the json file that goes with the dataset script by doing \r\n```\r\nnlp-cli test ./datasets/cnn_dailymail --save_infos --all_configs\r\n```\r\nIt will update the features metadata and the size of the dataset with your changes.",
"@lhoestq I ran that command.\r\n\r\... | 1,594,248,321,000 | 1,594,649,798,000 | 1,594,649,798,000 | CONTRIBUTOR | null | {
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} | The URL hashes are helpful for comparing results from other sources. | https://api.github.com/repos/huggingface/datasets/issues/357/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/356 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/356/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/356/comments | https://api.github.com/repos/huggingface/datasets/issues/356/events | https://github.com/huggingface/datasets/pull/356 | 653,537,388 | MDExOlB1bGxSZXF1ZXN0NDQ2NDM3MDQ5 | 356 | Add text dataset | {
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} | Usage:
```python
from nlp import load_dataset
dset = load_dataset("text", data_files="/path/to/file.txt")["train"]
```
I created a dummy_data.zip which contains three files: `train.txt`, `test.txt`, `dev.txt`. Each of these contains two lines. It passes
```bash
RUN_SLOW=1 pytest tests/test_dataset_common... | https://api.github.com/repos/huggingface/datasets/issues/356/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/355 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/355/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/355/comments | https://api.github.com/repos/huggingface/datasets/issues/355/events | https://github.com/huggingface/datasets/issues/355 | 653,451,013 | MDU6SXNzdWU2NTM0NTEwMTM= | 355 | can't load SNLI dataset | {
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"I just added the processed files of `snli` on our google storage, so that when you do `load_dataset` it can download the processed files from there :)\r\n\r\nWe are thinking about having available those processed files for more datasets in the future, because sometimes files aren't available (like for `snli`), or ... | 1,594,227,254,000 | 1,595,049,357,000 | 1,594,799,941,000 | CONTRIBUTOR | null | null | `nlp` seems to load `snli` from some URL based on nlp.stanford.edu. This subdomain is frequently down -- including right now, when I'd like to load `snli` in a Colab notebook, but can't.
Is there a plan to move these datasets to huggingface servers for a more stable solution?
Btw, here's the stack trace:
```
... | https://api.github.com/repos/huggingface/datasets/issues/355/timeline | null | false |
https://api.github.com/repos/huggingface/datasets/issues/354 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/354/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/354/comments | https://api.github.com/repos/huggingface/datasets/issues/354/events | https://github.com/huggingface/datasets/pull/354 | 653,357,617 | MDExOlB1bGxSZXF1ZXN0NDQ2MjkyMTc4 | 354 | More faiss control | {
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"> Ok, so we're getting rid of the `FaissGpuOptions`?\r\n\r\nWe support `device=...` because it's simple, but faiss GPU options can be used in so many ways (you can set different gpu options for the different parts of your index for example) that it's probably better to let the user create and configure its index a... | 1,594,219,520,000 | 1,594,288,494,000 | 1,594,288,491,000 | MEMBER | null | {
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} | Allow users to specify a faiss index they created themselves, as sometimes indexes can be composite for examples | https://api.github.com/repos/huggingface/datasets/issues/354/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/353 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/353/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/353/comments | https://api.github.com/repos/huggingface/datasets/issues/353/events | https://github.com/huggingface/datasets/issues/353 | 653,250,611 | MDU6SXNzdWU2NTMyNTA2MTE= | 353 | [Dataset requests] New datasets for Text Classification | {
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"Pinging @mariamabarham as well",
"- `nlp` has MR! It's called `rotten_tomatoes`\r\n- SST is part of GLUE, or is that just SST-2?\r\n- `nlp` also has `ag_news`, a popular news classification dataset\r\n\r\nI'd also like to see:\r\n- the Yahoo Answers topic classification dataset\r\n- the Kaggle Fake News classifi... | 1,594,210,678,000 | 1,603,165,283,000 | null | MEMBER | null | null | We are missing a few datasets for Text Classification which is an important field.
Namely, it would be really nice to add:
- TREC-6 dataset (see here for instance: https://pytorchnlp.readthedocs.io/en/latest/source/torchnlp.datasets.html#torchnlp.datasets.trec_dataset) **[done]**
- Yelp-5
- Movie review (Movie R... | https://api.github.com/repos/huggingface/datasets/issues/353/timeline | null | false |
https://api.github.com/repos/huggingface/datasets/issues/352 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/352/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/352/comments | https://api.github.com/repos/huggingface/datasets/issues/352/events | https://github.com/huggingface/datasets/pull/352 | 653,128,883 | MDExOlB1bGxSZXF1ZXN0NDQ2MTA1Mjky | 352 | 🐛[BugFix]fix seqeval | {
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"I think this is good but can you detail a bit the behavior before and after your fix?",
"examples:\r\n\r\ninput: `['B', 'I', 'I', 'O', 'B', 'I']`\r\nbefore: `[('B', 0, 0), ('I', 1, 2), ('B', 4, 4), ('I', 5, 5)]`\r\nafter: `[('_', 0, 2), ('_', 4, 5)]`\r\n\r\ninput: `['B-ARGM-LOC', 'I-ARGM-LOC', 'I-ARGM-LOC', 'O',... | 1,594,199,532,000 | 1,594,888,006,000 | 1,594,888,006,000 | CONTRIBUTOR | null | {
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} | Fix seqeval process labels such as 'B', 'B-ARGM-LOC' | https://api.github.com/repos/huggingface/datasets/issues/352/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/351 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/351/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/351/comments | https://api.github.com/repos/huggingface/datasets/issues/351/events | https://github.com/huggingface/datasets/pull/351 | 652,424,048 | MDExOlB1bGxSZXF1ZXN0NDQ1NDk0NTE4 | 351 | add pandas dataset | {
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} | Create a dataset from serialized pandas dataframes.
Usage:
```python
from nlp import load_dataset
dset = load_dataset("pandas", data_files="df.pkl")["train"]
``` | https://api.github.com/repos/huggingface/datasets/issues/351/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/350 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/350/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/350/comments | https://api.github.com/repos/huggingface/datasets/issues/350/events | https://github.com/huggingface/datasets/pull/350 | 652,398,691 | MDExOlB1bGxSZXF1ZXN0NDQ1NDczODYz | 350 | add from_pandas and from_dict | {
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} | I added two new methods to the `Dataset` class:
- `from_pandas()` to create a dataset from a pandas dataframe
- `from_dict()` to create a dataset from a dictionary (keys = columns)
It uses the `pa.Table.from_pandas` and `pa.Table.from_pydict` funcitons to do so.
It is also possible to specify the features types v... | https://api.github.com/repos/huggingface/datasets/issues/350/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/349 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/349/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/349/comments | https://api.github.com/repos/huggingface/datasets/issues/349/events | https://github.com/huggingface/datasets/pull/349 | 652,231,571 | MDExOlB1bGxSZXF1ZXN0NDQ1MzQwMTQ1 | 349 | Hyperpartisan news detection | {
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"Thank you so much for working on this! This is awesome!\r\n\r\nHow much would it help you if we would remove the manual request?\r\n\r\nWe are naturally interested in getting some broad idea of how many people and who are using our dataset. But if you consider hosting the dataset yourself, I would rather remove th... | 1,594,119,997,000 | 1,594,154,847,000 | 1,594,133,831,000 | CONTRIBUTOR | null | {
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} | Adding the hyperpartisan news detection dataset from PAN. This contains news article text, labelled with whether they're hyper-partisan and why kinds of biases they display.
Implementation notes:
- As with many PAN tasks, the data is hosted on [Zenodo](https://zenodo.org/record/1489920) and must be requested before... | https://api.github.com/repos/huggingface/datasets/issues/349/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/348 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/348/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/348/comments | https://api.github.com/repos/huggingface/datasets/issues/348/events | https://github.com/huggingface/datasets/pull/348 | 652,158,308 | MDExOlB1bGxSZXF1ZXN0NDQ1MjgwNjk3 | 348 | Add OSCAR dataset | {
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"@pjox I think the tests don't pass because you haven't provided any dummy data (`dummy_data.zip`).\r\n\r\n ",
"> @pjox I think the tests don't pass because you haven't provided any dummy data (`dummy_data.zip`).\r\n\r\nBut can I do the dummy data without running `python nlp-cli test datasets/<your-dataset-folder... | 1,594,113,727,000 | 1,620,079,628,000 | 1,612,865,959,000 | CONTRIBUTOR | null | {
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} | I don't know if tests pass, when I run them it tries to download the whole corpus which is around 3.5TB compressed and I don't have that kind of space. I'll really need some help with it 😅
Thanks! | https://api.github.com/repos/huggingface/datasets/issues/348/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/347 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/347/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/347/comments | https://api.github.com/repos/huggingface/datasets/issues/347/events | https://github.com/huggingface/datasets/issues/347 | 652,106,567 | MDU6SXNzdWU2NTIxMDY1Njc= | 347 | 'cp950' codec error from load_dataset('xtreme', 'tydiqa') | {
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"This is probably a Windows issue, we need to specify the encoding when `load_dataset()` reads the original CSV file.\r\nTry to find the `open()` statement called by `load_dataset()` and add an `encoding='utf-8'` parameter.\r\nSee issues #242 and #307 ",
"It should be in `xtreme.py:L755`:\r\n```python\r\n ... | 1,594,109,663,000 | 1,599,490,305,000 | 1,599,490,305,000 | CONTRIBUTOR | null | null | 
I guess the error is related to python source encoding issue that my PC is trying to decode the source code with wrong encoding-decoding tools, perhaps :
https://www.python.org/dev/peps/pep-0263/
I gues... | https://api.github.com/repos/huggingface/datasets/issues/347/timeline | null | false |
https://api.github.com/repos/huggingface/datasets/issues/346 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/346/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/346/comments | https://api.github.com/repos/huggingface/datasets/issues/346/events | https://github.com/huggingface/datasets/pull/346 | 652,044,151 | MDExOlB1bGxSZXF1ZXN0NDQ1MTg4MTUz | 346 | Add emotion dataset | {
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"I've tried it and am getting the same error as you.\r\n\r\nYou could use the text files rather than the pickle:\r\n```\r\nhttps://www.dropbox.com/s/ikkqxfdbdec3fuj/test.txt\r\nhttps://www.dropbox.com/s/1pzkadrvffbqw6o/train.txt\r\nhttps://www.dropbox.com/s/2mzialpsgf9k5l3/val.txt\r\n```\r\n\r\nThen you would get a... | 1,594,103,741,000 | 1,619,162,023,000 | 1,594,651,178,000 | MEMBER | null | {
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} | Hello 🤗 team!
I am trying to add an emotion classification dataset ([link](https://github.com/dair-ai/emotion_dataset)) to `nlp` but I am a bit stuck about what I should do when the URL for the dataset is not a ZIP file, but just a pickled `pandas.DataFrame` (see [here](https://www.dropbox.com/s/607ptdakxuh5i4s/me... | https://api.github.com/repos/huggingface/datasets/issues/346/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/345 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/345/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/345/comments | https://api.github.com/repos/huggingface/datasets/issues/345/events | https://github.com/huggingface/datasets/issues/345 | 651,761,201 | MDU6SXNzdWU2NTE3NjEyMDE= | 345 | Supporting documents in ELI5 | {
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"Hi @saverymax ! For licensing reasons, the original team was unable to release pre-processed CommonCrawl documents. Instead, they provided a script to re-create them from a CommonCrawl dump, but it unfortunately requires access to a medium-large size cluster:\r\nhttps://github.com/facebookresearch/ELI5#downloading... | 1,594,062,853,000 | 1,603,813,125,000 | 1,603,813,125,000 | NONE | null | null | I was attempting to use the ELI5 dataset, when I realized that huggingface does not provide the supporting documents (the source documents from the common crawl). Without the supporting documents, this makes the dataset about as useful for my project as a block of cheese, or some other more apt metaphor. According to ... | https://api.github.com/repos/huggingface/datasets/issues/345/timeline | null | false |
https://api.github.com/repos/huggingface/datasets/issues/344 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/344/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/344/comments | https://api.github.com/repos/huggingface/datasets/issues/344/events | https://github.com/huggingface/datasets/pull/344 | 651,495,246 | MDExOlB1bGxSZXF1ZXN0NDQ0NzQwMTIw | 344 | Search qa | {
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"Could you rebase from master just to make sure we won't break anything for `fever` pls @mariamabarham ?"
] | 1,594,038,196,000 | 1,594,889,896,000 | 1,594,889,896,000 | CONTRIBUTOR | null | {
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} | This PR adds the Search QA dataset used in **SearchQA: A New Q&A Dataset Augmented with Context from a Search Engine**. The dataset has the following config name:
- raw_jeopardy: raw data
- train_test_val: which is the splitted version
#336 | https://api.github.com/repos/huggingface/datasets/issues/344/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/343 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/343/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/343/comments | https://api.github.com/repos/huggingface/datasets/issues/343/events | https://github.com/huggingface/datasets/pull/343 | 651,419,630 | MDExOlB1bGxSZXF1ZXN0NDQ0Njc4NDEw | 343 | Fix nested tensorflow format | {
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} | In #339 and #337 we are thinking about adding a way to export datasets to tfrecords.
However I noticed that it was not possible to do `dset.set_format("tensorflow")` on datasets with nested features like `squad`. I fixed that using a nested map operations to convert features to `tf.ragged.constant`.
I also added ... | https://api.github.com/repos/huggingface/datasets/issues/343/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/342 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/342/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/342/comments | https://api.github.com/repos/huggingface/datasets/issues/342/events | https://github.com/huggingface/datasets/issues/342 | 651,333,194 | MDU6SXNzdWU2NTEzMzMxOTQ= | 342 | Features should be updated when `map()` changes schema | {
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"`dataset.column_names` are being updated but `dataset.features` aren't indeed..."
] | 1,594,022,603,000 | 1,595,499,316,000 | 1,595,499,316,000 | MEMBER | null | null | `dataset.map()` can change the schema and column names.
We should update the features in this case (with what is possible to infer). | https://api.github.com/repos/huggingface/datasets/issues/342/timeline | null | false |
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} | This PR add the FEVER dataset https://fever.ai/ used in with the paper: FEVER: a large-scale dataset for Fact Extraction and VERification (https://arxiv.org/pdf/1803.05355.pdf).
#336 | https://api.github.com/repos/huggingface/datasets/issues/341/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/340 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/340/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/340/comments | https://api.github.com/repos/huggingface/datasets/issues/340/events | https://github.com/huggingface/datasets/pull/340 | 650,533,920 | MDExOlB1bGxSZXF1ZXN0NDQ0MDA2Nzcy | 340 | Update cfq.py | {
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"Thanks @brainshawn for this update"
] | 1,593,775,399,000 | 1,593,779,630,000 | 1,593,779,630,000 | CONTRIBUTOR | null | {
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} | Make the dataset name consistent with in the paper: Compositional Freebase Question => Compositional Freebase Questions. | https://api.github.com/repos/huggingface/datasets/issues/340/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/339 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/339/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/339/comments | https://api.github.com/repos/huggingface/datasets/issues/339/events | https://github.com/huggingface/datasets/pull/339 | 650,156,468 | MDExOlB1bGxSZXF1ZXN0NDQzNzAyNTcw | 339 | Add dataset.export() to TFRecords | {
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"Really cool @jarednielsen !\r\nDo you think we can make it work with dataset with nested features like `squad` ?\r\n\r\nI just did a PR to fix `.set_format` for datasets with nested features, but as soon as it's merged we could try to make the conversion work on a dataset like `squad`.",
"For datasets with neste... | 1,593,717,987,000 | 1,595,409,372,000 | 1,595,409,372,000 | CONTRIBUTOR | null | {
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} | Fixes https://github.com/huggingface/nlp/issues/337
Some design decisions:
- Simplified the function API to not handle sharding. It writes the entire dataset as a single TFRecord file. This simplifies the function logic and users can use other functions (`select`, `shard`, etc) to handle custom sharding or splitt... | https://api.github.com/repos/huggingface/datasets/issues/339/timeline | null | true |
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} | These files get changed when I run `make style` on an unrelated PR. Upstreaming these changes so development on a different branch can be easier. | https://api.github.com/repos/huggingface/datasets/issues/338/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/337 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/337/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/337/comments | https://api.github.com/repos/huggingface/datasets/issues/337/events | https://github.com/huggingface/datasets/issues/337 | 650,035,887 | MDU6SXNzdWU2NTAwMzU4ODc= | 337 | [Feature request] Export Arrow dataset to TFRecords | {
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```python
# use these existing methods
ds = load_dataset("wikitext", "wik... | https://api.github.com/repos/huggingface/datasets/issues/337/timeline | null | false |
https://api.github.com/repos/huggingface/datasets/issues/336 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/336/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/336/comments | https://api.github.com/repos/huggingface/datasets/issues/336/events | https://github.com/huggingface/datasets/issues/336 | 649,914,203 | MDU6SXNzdWU2NDk5MTQyMDM= | 336 | [Dataset requests] New datasets for Open Question Answering | {
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"followers_url"... | null | [] | 1,593,694,983,000 | 1,594,890,262,000 | 1,594,890,262,000 | MEMBER | null | null | We are still a few datasets missing for Open-Question Answering which is currently a field in strong development.
Namely, it would be really nice to add:
- WebQuestions (Berant et al., 2013) [done]
- CuratedTrec (Baudis et al. 2015) [not open-source]
- MS-MARCO (NGuyen et al. 2016) [done]
- SearchQA (Dunn et al.... | https://api.github.com/repos/huggingface/datasets/issues/336/timeline | null | false |
https://api.github.com/repos/huggingface/datasets/issues/335 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/335/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/335/comments | https://api.github.com/repos/huggingface/datasets/issues/335/events | https://github.com/huggingface/datasets/pull/335 | 649,765,179 | MDExOlB1bGxSZXF1ZXN0NDQzMzgwMjI1 | 335 | BioMRC Dataset presented in BioNLP 2020 ACL Workshop | {
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"I fixed the issues that you pointed out, re-run all the test and pushed the fixed code :-)",
"```\r\n=================================== FAILURES ===================================\r\n___________________ AWSDatasetTest.test_load_dataset_pandas ____________________\r\n\r\nself = <tests.test_dataset_common.AWSDat... | 1,593,680,621,000 | 1,594,800,127,000 | 1,594,800,127,000 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/datasets/issues/334 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/334/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/334/comments | https://api.github.com/repos/huggingface/datasets/issues/334/events | https://github.com/huggingface/datasets/pull/334 | 649,661,791 | MDExOlB1bGxSZXF1ZXN0NDQzMjk1NjQ0 | 334 | Add dataset.shard() method | {
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"Great, done!"
] | 1,593,669,919,000 | 1,594,038,936,000 | 1,594,038,936,000 | CONTRIBUTOR | null | {
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} | Fixes https://github.com/huggingface/nlp/issues/312 | https://api.github.com/repos/huggingface/datasets/issues/334/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/333 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/333/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/333/comments | https://api.github.com/repos/huggingface/datasets/issues/333/events | https://github.com/huggingface/datasets/pull/333 | 649,236,516 | MDExOlB1bGxSZXF1ZXN0NDQyOTE1NDQ0 | 333 | fix variable name typo | {
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"Good catch :)\r\nI think there is another occurence that needs to be fixed in the second gist (line 4924 of the notebook file):\r\n```python\r\nbleu = nlp.load_metric(...)\r\n```",
"Was fixed in e16f79b5f7fc12a6a30c777722be46897a272e6f\r\nClosing it."
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https://api.github.com/repos/huggingface/datasets/issues/332 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/332/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/332/comments | https://api.github.com/repos/huggingface/datasets/issues/332/events | https://github.com/huggingface/datasets/pull/332 | 649,140,135 | MDExOlB1bGxSZXF1ZXN0NDQyODMwMzMz | 332 | Add wiki_dpr | {
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"The two configurations don't have the same sizes, I may change that so that they both have 21015300 examples for convenience, even though it's supposed to have 21015324 examples in total.\r\n\r\nOne configuration only has 21015300 examples because it seems that the embeddings of the last 24 examples are missing.",... | 1,593,623,520,000 | 1,594,038,077,000 | 1,594,038,076,000 | MEMBER | null | {
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} | Presented in the [Dense Passage Retrieval paper](https://arxiv.org/pdf/2004.04906.pdf), this dataset consists in 21M passages from the english wikipedia along with their 768-dim embeddings computed using DPR's context encoder.
Note on the implementation:
- There are two configs: with and without the embeddings (73G... | https://api.github.com/repos/huggingface/datasets/issues/332/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/331 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/331/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/331/comments | https://api.github.com/repos/huggingface/datasets/issues/331/events | https://github.com/huggingface/datasets/issues/331 | 648,533,199 | MDU6SXNzdWU2NDg1MzMxOTk= | 331 | Loading CNN/Daily Mail dataset produces `nlp.utils.info_utils.NonMatchingSplitsSizesError` | {
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"I couldn't reproduce on my side.\r\nIt looks like you were not able to generate all the examples, and you have the problem for each split train-test-validation.\r\nCould you try to enable logging, try again and send the logs ?\r\n```python\r\nimport logging\r\nlogging.basicConfig(level=logging.INFO)\r\n```",
"he... | 1,593,555,693,000 | 1,594,299,820,000 | 1,594,299,820,000 | CONTRIBUTOR | null | null | ```
>>> import nlp
>>> nlp.load_dataset('cnn_dailymail', '3.0.0')
Downloading and preparing dataset cnn_dailymail/3.0.0 (download: 558.32 MiB, generated: 1.26 GiB, total: 1.81 GiB) to /u/jm8wx/.cache/huggingface/datasets/cnn_dailymail/3.0.0/3.0.0...
Traceback (most recent call last):
File "<stdin>", line 1, in... | https://api.github.com/repos/huggingface/datasets/issues/331/timeline | null | false |
https://api.github.com/repos/huggingface/datasets/issues/330 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/330/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/330/comments | https://api.github.com/repos/huggingface/datasets/issues/330/events | https://github.com/huggingface/datasets/pull/330 | 648,525,720 | MDExOlB1bGxSZXF1ZXN0NDQyMzIxMjEw | 330 | Doc red | {
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} | Adding [DocRED](https://github.com/thunlp/DocRED) - a relation extraction dataset which tests document-level RE. A few implementation notes:
- There are 2 separate versions of the training set - *annotated* and *distant*. Instead of `nlp.Split.Train` I've used the splits `"train_annotated"` and `"train_distant"` to ... | https://api.github.com/repos/huggingface/datasets/issues/330/timeline | null | true |
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"Hi, can you give details on your environment/os/packages versions/etc?",
"Environment is Ubuntu 18.04, Python 3.7.5, nlp==0.3.0, filelock=3.0.12.\r\n\r\nThe external volume is Amazon FSx for Lustre, and it by default creates files with limited permissions. My working theory is that FileLock creates a lockfile th... | 1,593,546,331,000 | 1,593,586,558,000 | 1,593,552,786,000 | CONTRIBUTOR | null | null | I'm downloading a dataset successfully with
`load_dataset("wikitext", "wikitext-2-raw-v1")`
But when I attempt to cache it on an external volume, it hangs indefinitely:
`load_dataset("wikitext", "wikitext-2-raw-v1", cache_dir="/fsx") # /fsx is an external volume mount`
The filesystem when hanging looks like thi... | https://api.github.com/repos/huggingface/datasets/issues/329/timeline | null | false |
https://api.github.com/repos/huggingface/datasets/issues/328 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/328/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/328/comments | https://api.github.com/repos/huggingface/datasets/issues/328/events | https://github.com/huggingface/datasets/issues/328 | 648,326,841 | MDU6SXNzdWU2NDgzMjY4NDE= | 328 | Fork dataset | {
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"To be able to generate the Arrow dataset you need to either use our csv or json utilities `load_dataset(\"json\", data_files=my_json_files)` OR write your own custom dataset script (you can find some inspiration from the [squad](https://github.com/huggingface/nlp/blob/master/datasets/squad/squad.py) script for exa... | 1,593,535,373,000 | 1,594,071,839,000 | 1,594,071,839,000 | NONE | null | null | We have a multi-task learning model training I'm trying to convert to using the Arrow-based nlp dataset.
We're currently training a custom TensorFlow model but the nlp paradigm should be a bridge for us to be able to use the wealth of pre-trained models in Transformers.
Our preprocessing flow parses raw text and... | https://api.github.com/repos/huggingface/datasets/issues/328/timeline | null | false |
https://api.github.com/repos/huggingface/datasets/issues/327 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/327/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/327/comments | https://api.github.com/repos/huggingface/datasets/issues/327/events | https://github.com/huggingface/datasets/pull/327 | 648,312,858 | MDExOlB1bGxSZXF1ZXN0NDQyMTQyOTQw | 327 | set seed for suffling tests | {
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} | Some tests were randomly failing because of a missing seed in a test for `train_test_split(shuffle=True)` | https://api.github.com/repos/huggingface/datasets/issues/327/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/326 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/326/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/326/comments | https://api.github.com/repos/huggingface/datasets/issues/326/events | https://github.com/huggingface/datasets/issues/326 | 648,126,103 | MDU6SXNzdWU2NDgxMjYxMDM= | 326 | Large dataset in Squad2-format | {
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"I'm pretty sure you can get some inspiration from the squad_v2 script. It looks like the dataset is quite big so it will take some time for the users to generate it, but it should be reasonable.\r\n\r\nAlso you are saying that you are still making the dataset grow in size right ?\r\nIt's probably good practice to ... | 1,593,519,539,000 | 1,594,285,310,000 | 1,594,285,310,000 | NONE | null | null | At the moment we are building an large question answering dataset and think about sharing it with the huggingface community.
Caused the computing power we splitted it into multiple tiles, but they are all in the same format.
Right now the most important facts about are this:
- Contexts: 1.047.671
- questions: 1.677... | https://api.github.com/repos/huggingface/datasets/issues/326/timeline | null | false |
https://api.github.com/repos/huggingface/datasets/issues/325 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/325/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/325/comments | https://api.github.com/repos/huggingface/datasets/issues/325/events | https://github.com/huggingface/datasets/pull/325 | 647,601,592 | MDExOlB1bGxSZXF1ZXN0NDQxNTk3NTgw | 325 | Add SQuADShifts dataset | {
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"Very cool to have this dataset, thank you for adding it :)"
] | 1,593,457,876,000 | 1,593,536,851,000 | 1,593,536,851,000 | CONTRIBUTOR | null | {
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} | This PR adds the four new variants of the SQuAD dataset used in [The Effect of Natural Distribution Shift on Question Answering Models](https://arxiv.org/abs/2004.14444) to facilitate evaluating model robustness to distribution shift. | https://api.github.com/repos/huggingface/datasets/issues/325/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/324 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/324/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/324/comments | https://api.github.com/repos/huggingface/datasets/issues/324/events | https://github.com/huggingface/datasets/issues/324 | 647,525,725 | MDU6SXNzdWU2NDc1MjU3MjU= | 324 | Error when calculating glue score | {
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"The glue metric for cola is a metric for classification. It expects label ids as integers as inputs.",
"I want to evaluate a sentence pair whether they are semantically equivalent, so I used MRPC and it gives the same error, does that mean we have to encode the sentences and parse as input?\r\n\r\nusing BertToke... | 1,593,449,628,000 | 1,594,286,014,000 | 1,594,286,014,000 | NONE | null | null | I was trying glue score along with other metrics here. But glue gives me this error;
```
import nlp
glue_metric = nlp.load_metric('glue',name="cola")
glue_score = glue_metric.compute(predictions, references)
```
```
---------------------------------------------------------------------------
--------------... | https://api.github.com/repos/huggingface/datasets/issues/324/timeline | null | false |
https://api.github.com/repos/huggingface/datasets/issues/323 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/323/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/323/comments | https://api.github.com/repos/huggingface/datasets/issues/323/events | https://github.com/huggingface/datasets/pull/323 | 647,521,308 | MDExOlB1bGxSZXF1ZXN0NDQxNTMxOTY3 | 323 | Add package path to sys when downloading package as github archive | {
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"Sorry for the long diff, everything after the imports comes from `black` for code quality :/ ",
" I think it's fine and I can't think of another way to make the import work anyways.\r\n\r\nMaybe we can have the `sys.path` behavior inside `prepare_module` instead ? Currently it seems to come out of nowhere in the... | 1,593,449,161,000 | 1,596,117,623,000 | 1,596,117,623,000 | MEMBER | null | {
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} | This fixes the `coval.py` metric so that imports within the downloaded module work correctly. We can use a similar trick to add the BLEURT metric (@ankparikh)
@thomwolf not sure how you feel about adding to the `PYTHONPATH` from the script. This is the only way I could make it work with my understanding of `importli... | https://api.github.com/repos/huggingface/datasets/issues/323/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/322 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/322/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/322/comments | https://api.github.com/repos/huggingface/datasets/issues/322/events | https://github.com/huggingface/datasets/pull/322 | 647,483,850 | MDExOlB1bGxSZXF1ZXN0NDQxNTAyMjc2 | 322 | output nested dict in get_nearest_examples | {
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} | As we are using a columnar format like arrow as the backend for datasets, we expect to have a dictionary of columns when we slice a dataset like in this example:
```python
my_examples = dataset[0:10]
print(type(my_examples))
# >>> dict
print(my_examples["my_column"][0]
# >>> this is the first element of the colum... | https://api.github.com/repos/huggingface/datasets/issues/322/timeline | null | true |
https://api.github.com/repos/huggingface/datasets/issues/321 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/321/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/321/comments | https://api.github.com/repos/huggingface/datasets/issues/321/events | https://github.com/huggingface/datasets/issues/321 | 647,271,526 | MDU6SXNzdWU2NDcyNzE1MjY= | 321 | ERROR:root:mwparserfromhell | {
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"It looks like it comes from `mwparserfromhell`.\r\n\r\nWould it be possible to get the bad `section` that causes this issue ? The `section` string is from `datasets/wikipedia.py:L548` ? You could just add a `try` statement and print the section if the line `section_text.append(section.strip_code().strip())` crashe... | 1,593,429,043,000 | 1,595,521,714,000 | null | NONE | null | null | Hi,
I am trying to download some wikipedia data but I got this error for spanish "es" (but there are maybe some others languages which have the same error I haven't tried all of them ).
`ERROR:root:mwparserfromhell ParseError: This is a bug and should be reported. Info: C tokenizer exited with non-empty token sta... | https://api.github.com/repos/huggingface/datasets/issues/321/timeline | null | false |
https://api.github.com/repos/huggingface/datasets/issues/320 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/320/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/320/comments | https://api.github.com/repos/huggingface/datasets/issues/320/events | https://github.com/huggingface/datasets/issues/320 | 647,188,167 | MDU6SXNzdWU2NDcxODgxNjc= | 320 | Blog Authorship Corpus, Non Matching Splits Sizes Error, nlp viewer | {
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] | closed | false | null | [] | null | [
"I wonder if this means downloading failed? That corpus has a really slow server.",
"This dataset seems to have a decoding problem that results in inconsistencies in the number of generated examples.\r\nSee #215.\r\nThat's why we end up with a `NonMatchingSplitsSizesError `."
] | 1,593,416,195,000 | 1,593,441,882,000 | 1,593,441,882,000 | CONTRIBUTOR | null | null | Selecting `blog_authorship_corpus` in the nlp viewer throws the following error:
```
NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='train', num_bytes=610252351, num_examples=532812, dataset_name='blog_authorship_corpus'), 'recorded': SplitInfo(name='train', num_bytes=614706451, num_examples=535568, dat... | https://api.github.com/repos/huggingface/datasets/issues/320/timeline | null | false |
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