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https://api.github.com/repos/huggingface/datasets/issues/1798 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1798/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1798/comments | https://api.github.com/repos/huggingface/datasets/issues/1798/events | https://github.com/huggingface/datasets/pull/1798 | 797,766,818 | MDExOlB1bGxSZXF1ZXN0NTY0Njk2NjE1 | 1,798 | Add Arabic sarcasm dataset | {
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"@lhoestq thanks for the comments - I believe these are now addressed. I re-generated the datasets_info.json and dummy data"
] | 1,612,114,735,000 | 1,612,989,553,000 | 1,612,348,554,000 | CONTRIBUTOR | null | This MIT license dataset: https://github.com/iabufarha/ArSarcasm
Via https://sites.google.com/view/ar-sarcasm-sentiment-detection/ | {
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"Hi ! For future references let me add a link to our discussion here : https://github.com/huggingface/datasets/issues/759#issuecomment-770684693\r\n\r\nLet me know if you manage to fix your proxy issue or if we can do something on our end to help you :)"
] | 1,611,991,965,000 | 1,628,100,577,000 | 1,628,100,577,000 | NONE | null | Hi
I am hitting to the error, help me and thanks.
`train_data = datasets.load_dataset("xsum", split="train")`
`ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.0.2/datasets/xsum/xsum.py` | {
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"When I use the filter on the arrow table directly, it works like butter. But I can't find a way to update the table in `Dataset` object.\r\n\r\n```\r\nds_table = dataset.data.filter(mask=dataset['flag'])\r\n```",
"@thomwolf @lhoestq can you guys please take a look and recommend some solution.",
"Hi ! Currently... | 1,611,979,759,000 | 1,613,668,164,000 | null | NONE | null | I have a dataset with 50M rows.
For pre-processing, I need to tokenize this and filter rows with the large sequence.
My tokenization took roughly 12mins. I used `map()` with batch size 1024 and multi-process with 96 processes.
When I applied the `filter()` function it is taking too much time. I need to filter se... | {
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"This PR is amazing!!!\r\n\r\nI only looked at `arrow_dataset.py` and `formatting/formatting.py` but those look good to me.\r\n\r\nMy only (tiny) concern is the name of the function: I don't think it's self-evident that `set_format` applies a generic transformation, and some people might not look too far into the d... | 1,611,938,153,000 | 1,612,518,847,000 | 1,612,518,846,000 | MEMBER | null | Hi !
This PR refactors the way data are extracted from pyarrow tables to extend it to the use of custom formatting functions.
While the internal storage of the dataset is always the Apache Arrow format, by setting a specific format on a dataset, you can cast the output of `datasets.Dataset.__getitem__` in NumPy/p... | {
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"following_url"... | [] | 1,611,934,395,000 | 1,611,937,899,000 | 1,611,937,898,000 | MEMBER | null | The dataset was added in #1761 but not in the right directory. I'm moving it to /datasets | {
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- duplicated attributes
- format fix | {
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"I am wondering how to test their difference...",
"> ring how to test their difference...\r\n\r\nHmm I don't think pyarrow exposes an API to check if a Table comes from a file that is memory-mapped. In particular since all the buffer/memory logic is in the C++ part of pyarrow.\r\n\r\nOtherwise we can still check ... | 1,611,931,190,000 | 1,613,139,208,000 | 1,613,139,208,000 | MEMBER | null | Allow loading datasets either from:
- memory-mapped file (current implementation)
- from file descriptor, copying data to physical memory
Close #708 | {
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"following_url"... | [] | 1,611,930,366,000 | 1,611,946,270,000 | 1,611,939,907,000 | CONTRIBUTOR | null | Now you can set `train_size` to the whole dataset size via `train_size = -1` and login writes not `Training the index with the first -1 vectors` but (for example) `Training the index with the first 16123 vectors`. And maybe more than dataset length. Logging will be correct | {
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"Hi !\r\n\r\nApache Beam is a framework used to define data transformation pipelines. These pipeline can then be run in many runtimes: DataFlow, Spark, Flink, etc. There also exist a local runner called the DirectRunner.\r\nWikipedia is a dataset that requires some parsing, so to allow the processing to be run on t... | 1,611,908,244,000 | 1,616,674,251,000 | null | CONTRIBUTOR | null | ```py
import datasets
wiki = datasets.load_dataset('wikipedia', '20200501.ja', cache_dir='./datasets')
```
then `ModuleNotFoundError: No module named 'apache_beam'` happend.
The error doesn't appear when it's '20200501.en'.
I don't know Apache Beam, but according to #498 it isn't necessary when it's saved to lo... | {
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"following_url"... | [] | 1,611,856,897,000 | 1,611,857,636,000 | 1,611,857,636,000 | MEMBER | null | This tiny PR fixes a typo introduced in https://github.com/huggingface/datasets/pull/1726 which prevents loading new metrics | {
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https://api.github.com/repos/huggingface/datasets/issues/1787 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1787/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1787/comments | https://api.github.com/repos/huggingface/datasets/issues/1787/events | https://github.com/huggingface/datasets/pull/1787 | 795,485,842 | MDExOlB1bGxSZXF1ZXN0NTYyODI1NTI3 | 1,787 | Update the CommonGen citation information | {
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https://api.github.com/repos/huggingface/datasets/issues/1786 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1786/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1786/comments | https://api.github.com/repos/huggingface/datasets/issues/1786/events | https://github.com/huggingface/datasets/issues/1786 | 795,462,816 | MDU6SXNzdWU3OTU0NjI4MTY= | 1,786 | How to use split dataset | {
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"By default, all 3 splits will be loaded if you run the following:\r\n\r\n```python\r\nfrom datasets import load_dataset\r\ndataset = load_dataset(\"lambada\")\r\nprint(dataset[\"train\"])\r\nprint(dataset[\"valid\"])\r\n\r\n```\r\n\r\nIf you wanted to do load this manually, you could do this:\r\n\r\n```python\r\nf... | 1,611,783,467,000 | 1,619,191,059,000 | 1,619,191,059,000 | NONE | null | 
Hey,
I want to split the lambada dataset into corpus, test, train and valid txt files (like penn treebank) but I am not able to achieve this. What I am doing is, executing the lambada.py file in my pro... | {
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https://api.github.com/repos/huggingface/datasets/issues/1785 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1785/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1785/comments | https://api.github.com/repos/huggingface/datasets/issues/1785/events | https://github.com/huggingface/datasets/issues/1785 | 795,458,856 | MDU6SXNzdWU3OTU0NTg4NTY= | 1,785 | Not enough disk space (Needed: Unknown size) when caching on a cluster | {
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"Hi ! \r\n\r\nWhat do you mean by \"disk_usage(\".\").free` can't compute on the cluster's shared disk\" exactly ?\r\nDoes it return 0 ?",
"Yes, that's right. It shows 0 free space even though there is. I suspect it might have to do with permissions on the shared disk.\r\n\r\n```python\r\n>>> disk_usage(\".\")\r\... | 1,611,783,059,000 | 1,611,968,876,000 | 1,611,968,876,000 | CONTRIBUTOR | null | I'm running some experiments where I'm caching datasets on a cluster and accessing it through multiple compute nodes. However, I get an error when loading the cached dataset from the shared disk.
The exact error thrown:
```bash
>>> load_dataset(dataset, cache_dir="/path/to/cluster/shared/path")
OSError: Not eno... | {
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"Hi !\r\n\r\nThe `json` dataset script does support this format. For example loading a dataset with this format works on my side:\r\n```json\r\n{\"key1\":11, \"key2\":12, \"key3\":13}\r\n{\"key1\":21, \"key2\":22, \"key3\":23}\r\n```\r\n\r\nCan you show the full stacktrace please ? Also which version of datasets an... | 1,611,706,762,000 | 1,612,082,838,000 | 1,612,082,838,000 | CONTRIBUTOR | null | Hello :),
I have been trying to load data using a JSON file. Based on the [docs](https://huggingface.co/docs/datasets/loading_datasets.html#json-files), the following format is supported:
```json
{"key1":11, "key2":12, "key3":13}
{"key1":21, "key2":22, "key3":23}
```
But, when I try loading a dataset with th... | {
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"Hi @ChewKokWah,\r\n\r\nWe're working on it! In the meantime, you can still find the dataset explorer at the following URL: https://huggingface.co/datasets/viewer/",
"Glad to see that it still exist, this existing one is more than good enough for me, it is feature rich, simple to use and concise. \r\nHope similar... | 1,611,693,542,000 | 1,612,187,924,000 | 1,612,187,924,000 | NONE | null | In the Older version of the Dataset, there are a useful Dataset Explorer that allow user to visualize the examples (training, test and validation) of a particular dataset, it is no longer there in current version.
Hope HuggingFace can re-enable the feature that at least allow viewing of the first 20 examples of a ... | {
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"following_url"... | [] | 1,611,661,631,000 | 1,611,669,050,000 | 1,611,669,049,000 | MEMBER | null | Update the minimum version to >=0.17.1 in the pyarrow version check and update the message.
I also moved the check at the top of the __init__.py | {
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"Hi ! I'm not able to reproduce the issue. Can you try restarting your runtime ?\r\n\r\nThe PyExtensionType is available in pyarrow starting 0.17.1 iirc. If restarting your runtime doesn't fix this, can you try updating pyarrow ?\r\n```\r\npip install pyarrow --upgrade\r\n```",
"We should bump up the version test... | 1,611,634,715,000 | 1,611,661,656,000 | null | NONE | null | I'm using Colab. And suddenly this morning, there is this error. Have a look below!
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"Hi ! The error you get is the result of some verifications the library is doing when loading a dataset that already has some metadata in the dataset_infos.json. You can ignore the verifications with \r\n```\r\npython datasets-cli test datasets/scifact --save_infos --all_configs --ignore_verifications\r\n```\r\nThi... | 1,611,629,346,000 | 1,611,859,680,000 | 1,611,829,185,000 | CONTRIBUTOR | null | Hi,
I'm following up this [issue](https://github.com/huggingface/datasets/issues/1717). I'm the SciFact dataset creator, and I'm trying to update the SciFact data url in your repo. Thanks again for adding the dataset!
Basically, I'd just like to change the `_URL` to `"https://scifact.s3-us-west-2.amazonaws.com/re... | {
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"following_url"... | [] | 1,611,592,949,000 | 1,611,656,420,000 | 1,611,656,419,000 | MEMBER | null | As noticed in #1718 , when a function used for processing with `map` is moved inside its python file, then the change of line number causes the caching mechanism to consider it as a different function. Therefore in this case, it recomputes everything.
This is because we were not ignoring the line number definition f... | {
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"@lhoestq sorry I opened a new pull request because of some issues with the previous code base. This pull request is originally from #1364",
"Excellent comments. Thanks for those valuable suggestions. I changed everything as you have pointed out :) ",
"I've copied the same template as NarrativeQA now. Please le... | 1,611,588,151,000 | 1,611,912,914,000 | 1,611,912,891,000 | CONTRIBUTOR | null | Submitting the manual version of Narrative QA script which requires a manual download from the original repository | {
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https://api.github.com/repos/huggingface/datasets/issues/1777 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1777/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1777/comments | https://api.github.com/repos/huggingface/datasets/issues/1777/events | https://github.com/huggingface/datasets/issues/1777 | 793,273,770 | MDU6SXNzdWU3OTMyNzM3NzA= | 1,777 | GPT2 MNLI training using run_glue.py | {
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"following_url"... | [] | 1,611,572,032,000 | 1,611,573,173,000 | 1,611,573,173,000 | NONE | null | Edit: I'm closing this because I actually meant to post this in `transformers `not `datasets`
Running this on Google Colab,
```
!python run_glue.py \
--model_name_or_path gpt2 \
--task_name mnli \
--do_train \
--do_eval \
--max_seq_length 128 \
--per_gpu_train_batch_size 10 \
--gradient_accu... | {
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"We are very actively working on this. How does your dataset look like in practice (number/size/type of files)?",
"It's a text file with many lines (about 1B) of Chinese sentences. I use it to train language model using https://github.com/huggingface/transformers/blob/master/examples/language-modeling/run_mlm_wwm... | 1,611,480,504,000 | 1,621,484,158,000 | 1,621,484,158,000 | NONE | null | I know we can use `Datasets.map` to preprocess a dataset, but I'm using it with very large corpus which generates huge cache file (several TB cache from a 400 GB text file). I have no disk large enough to save it. Can we preprocess a dataset on the fly without generating cache?
BTW, I tried raising `writer_batch_si... | {
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"It seems that selecting a subset of colums directly from the dataset, i.e., dataset[\"column\"], is slow.",
"I was wrong, ```dataset[\"column\"]``` is fast."
] | 1,611,474,871,000 | 1,611,481,839,000 | 1,611,481,839,000 | CONTRIBUTOR | null | For a large dataset that does not fits the memory, how can I select only a subset of features from each example?
If I iterate over the dataset and then select the subset of features one by one, the resulted memory usage will be huge. Any ways to solve this?
Thanks | {
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"Hi ! Thanks for reporting.\r\nI am working on changes in the way data are sliced from arrow. I can probably fix your issue with the changes I'm doing.\r\nIf you have some code to reproduce the issue it would be nice so I can make sure that this case will be supported :)\r\nI'll make a PR in a few days ",
"Good i... | 1,611,468,952,000 | 1,611,531,378,000 | null | NONE | null | Hi,
see below error:
```
AssertionError: Requested slice [:10000000000000000] incompatible with 20 examples.
``` | {
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"Looks like an issue with your csv file. Did you use the right delimiter ?\r\nApparently at line 37 the CSV reader from pandas reads 2 fields instead of 1.",
"Note that you can pass any argument you would pass to `pandas.read_csv` as kwargs to `load_dataset`. For example you can do\r\n```python\r\nfrom datasets i... | 1,611,456,825,000 | 1,630,918,486,000 | 1,628,100,781,000 | NONE | null | Hi,
I need to load a dataset, I use these commands:
```
from datasets import load_dataset
dataset = load_dataset('csv', data_files={'train': 'sick/train.csv',
'test': 'sick/test.csv',
'validation': 'sick/validation.csv'})
prin... | {
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"following_url"... | [] | 1,611,454,531,000 | 1,612,540,165,000 | 1,612,540,165,000 | NONE | null | Hi
It would be great to include SICK dataset.
## Adding a Dataset
- **Name:** SICK
- **Description:** a well known entailment dataset
- **Paper:** http://marcobaroni.org/composes/sick.html
- **Data:** http://marcobaroni.org/composes/sick.html
- **Motivation:** this is an important NLI benchmark
Instruction... | {
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"I temporary manually download csv.py as custom dataset loading script",
"Indeed in 1.2.1 the script to process csv file is downloaded. Starting from the next release though we include the csv processing directly in the library.\r\nSee PR #1726 \r\nWe'll do a new release soon :)",
"Thanks."
] | 1,611,453,232,000 | 1,611,529,589,000 | 1,611,529,589,000 | NONE | null | Hi,
When I load_dataset from local csv files, below error happened, looks raw.githubusercontent.com was blocked by the chinese government. But why it need to download csv.py? should it include when pip install the dataset?
```
Traceback (most recent call last):
File "/home/tom/pyenv/pystory/lib/python3.6/site-p... | {
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"Hi ! Currently we don't have a way to `zip` datasets but we plan to add this soon :)\r\nFor now you'll need to use `map` to add the fields from one dataset to the other. See the comment here for more info : https://github.com/huggingface/datasets/issues/853#issuecomment-727872188",
"Good to hear.\r\nCurrently I ... | 1,611,451,566,000 | 1,611,531,834,000 | null | NONE | null | to combine 2 dataset by one-one map like ds = zip(ds1, ds2):
ds1: {'text'}, ds2: {'text'}, combine ds:{'src', 'tgt'}
or different feature:
ds1: {'src'}, ds2: {'tgt'}, combine ds:{'src', 'tgt'} | {
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"More information: `run_mlm.py` will raise same error when `data_args.line_by_line==True`\r\n\r\nhttps://github.com/huggingface/transformers/blob/9152f16023b59d262b51573714b40325c8e49370/examples/language-modeling/run_mlm.py#L300\r\n",
"Hi ! What version of python and datasets do you have ? And also what version ... | 1,611,396,780,000 | 1,611,570,237,000 | null | NONE | null | It may be a bug of multiprocessing with Datasets, when I disable the multiprocessing by set num_proc to None, everything works fine.
The script I use is https://github.com/huggingface/transformers/blob/master/examples/language-modeling/run_mlm_wwm.py
Script args:
```
--model_name_or_path
../../../model/chine... | {
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"following_url"... | [] | 1,611,333,800,000 | 1,612,096,390,000 | 1,611,566,099,000 | CONTRIBUTOR | null | Hi,
This was discussed in Issue #1762 where the docs didn't mention that keyword arguments to `datasets.Dataset.set_format()` are allowed.
To prevent people from having to check the code/method docs, I just added a couple of lines in the docs.
Please let me know your thoughts on this.
Thanks,
Gunjan
@lho... | {
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"> Awesome thank you !\r\n> \r\n> The dummy data are quite big but it was expected given that the raw files are flac files.\r\n> Given that the script doesn't even read the flac files I think we can remove them. Or maybe use empty flac files (see [here](https://hydrogenaud.io/index.php?topic=118685.0) for example).... | 1,611,327,277,000 | 1,611,607,087,000 | 1,611,607,062,000 | MEMBER | null | This PR adds the librispeech asr dataset: https://www.tensorflow.org/datasets/catalog/librispeech
There are 2 configs: "clean" and "other" whereas there are two "train" datasets for "clean", hence the name "train.100" and "train.360".
As suggested by @lhoestq, due to the enormous size of the dataset in `.arrow` f... | {
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"Hi ! To avoid collisions you can specify a `experiment_id` when instantiating your metric using `load_metric`. It will replace \"default_experiment\" with the experiment id that you provide in the arrow filename. \r\n\r\nAlso when two `experiment_id` collide we're supposed to detect it using our locking mechanism.... | 1,611,325,375,000 | 1,612,262,286,000 | 1,612,262,286,000 | NONE | null | I got the following error when running two different programs that both compute sacreblue metrics. It seems that both read/and/write to the same location (.cache/huggingface/metrics/sacrebleu/default/default_experiment-1-0.arrow) where it caches the batches:
```
File "train_matching_min.py", line 160, in <module>ch... | {
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"Instead of:\r\n```python\r\ndataloader = torch.utils.data.DataLoader(encoded_dataset, batch_sampler=32)\r\n```\r\nIt should be:\r\n```python\r\ndataloader = torch.utils.data.DataLoader(encoded_dataset, batch_size=32)\r\n```\r\n\r\n`batch_sampler` accepts a Sampler object or an Iterable, so you get an error.",
"@... | 1,611,269,805,000 | 1,638,879,753,000 | 1,611,373,454,000 | NONE | null | I have a Dataset that I've mapped a tokenizer over:
```
encoded_dataset.set_format(type='torch',columns=['attention_mask','input_ids','token_type_ids'])
encoded_dataset[:1]
```
```
{'attention_mask': tensor([[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]),
'input_ids': tensor([[ 101, 178, 1198, 1400, 1714, 22233, 2... | {
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"Academic WIFI was blocking."
] | 1,611,262,569,000 | 1,611,262,819,000 | 1,611,262,802,000 | NONE | null | Today, I am getting connection issues while loading a dataset and the metric.
```
Traceback (most recent call last):
File "src/train.py", line 180, in <module>
train_dataset, dev_dataset, test_dataset = create_race_dataset()
File "src/train.py", line 130, in create_race_dataset
train_dataset = load_da... | {
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https://api.github.com/repos/huggingface/datasets/issues/1763 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1763/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1763/comments | https://api.github.com/repos/huggingface/datasets/issues/1763/events | https://github.com/huggingface/datasets/pull/1763 | 791,389,763 | MDExOlB1bGxSZXF1ZXN0NTU5NDU3MTY1 | 1,763 | PAWS-X: Fix csv Dictreader splitting data on quotes | {
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"following_url"... | [] | 1,611,253,261,000 | 1,611,310,473,000 | 1,611,310,425,000 | CONTRIBUTOR | null |
```python
from datasets import load_dataset
# load english paws-x dataset
datasets = load_dataset('paws-x', 'en')
print(len(datasets['train'])) # outputs 49202 but official dataset has 49401 pairs
print(datasets['train'].unique('label')) # outputs [1, 0, -1] but labels are binary [0,1]
... | {
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https://api.github.com/repos/huggingface/datasets/issues/1762 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1762/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1762/comments | https://api.github.com/repos/huggingface/datasets/issues/1762/events | https://github.com/huggingface/datasets/issues/1762 | 791,226,007 | MDU6SXNzdWU3OTEyMjYwMDc= | 1,762 | Unable to format dataset to CUDA Tensors | {
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"Hi ! You can get CUDA tensors with\r\n\r\n```python\r\ndataset.set_format(\"torch\", columns=columns, device=\"cuda\")\r\n```\r\n\r\nIndeed `set_format` passes the `**kwargs` to `torch.tensor`",
"Hi @lhoestq,\r\n\r\nThanks a lot. Is this true for all format types?\r\n\r\nAs in, for 'torch', I can have `**kwargs`... | 1,611,243,083,000 | 1,612,250,002,000 | 1,612,250,002,000 | CONTRIBUTOR | null | Hi,
I came across this [link](https://huggingface.co/docs/datasets/torch_tensorflow.html) where the docs show show to convert a dataset to a particular format. I see that there is an option to convert it to tensors, but I don't see any option to convert it to CUDA tensors.
I tried this, but Dataset doesn't suppor... | {
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"Thanks for the feedback. All your comments have been addressed!",
"Thank you for your constructive feedback! I now know how to best format future datasets that our team plans to publish in the near future :)",
"Awesome ! Looking forward to it :) ",
"Hi @lhoestq ! One last question. Our research team would li... | 1,611,239,352,000 | 1,612,449,168,000 | 1,611,669,031,000 | CONTRIBUTOR | null | My collaborators and I within the Affective Computing team at Telecom Paris would like to re-submit our spoken dialogue dataset for publication.
This is a new pull request relative to the [previously closed request](https://github.com/huggingface/datasets/pull/1712) which was reviewed by @lhoestq.
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https://api.github.com/repos/huggingface/datasets/issues/1760 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1760/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1760/comments | https://api.github.com/repos/huggingface/datasets/issues/1760/events | https://github.com/huggingface/datasets/pull/1760 | 791,110,857 | MDExOlB1bGxSZXF1ZXN0NTU5MjE3MjY0 | 1,760 | More tags | {
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"Conll has `multilingual` but is only tagged as `en`",
"good catch, that was a bad copy paste x)"
] | 1,611,237,010,000 | 1,611,308,401,000 | 1,611,308,400,000 | MEMBER | null | Since the hub v2 is going to be released soon I figured it would be great to add the missing tags at least for some of the datasets of reference listed [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md#write-the-loadingprocessing-code) | {
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"Hi !\r\nFrom what pickle file fo you get this ?\r\nI guess you mean the dataset loaded using `load_dataset` ?",
"yes sorry, I used the `load_dataset`function and saved the data to a pickle file so I don't always have to reload it and are able to work offline. ",
"The wikipedia articles are processed using the ... | 1,611,229,635,000 | 1,611,249,731,000 | 1,611,249,666,000 | NONE | null | Hey guys,
I am using the https://github.com/huggingface/datasets/tree/master/datasets/wikipedia dataset.
Unfortunately, I found out that there is an incompleteness for the German dataset.
For reasons unknown to me, the number of inhabitants has been removed from many pages:
Thorey-sur-Ouche has 128 inhabitants a... | {
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"Hi !\r\nI tried your code on my side and I was able to workaround this issue by waiting a few seconds before querying the index.\r\nMaybe this is because the index is not updated yet on the ElasticSearch side ?",
"Thanks for the feedback! I added a 30 second \"sleep\" and that seemed to work well!"
] | 1,611,195,997,000 | 1,611,275,150,000 | 1,611,275,150,000 | NONE | null | I am trying to use elastic search to retrieve the indices of items in the dataset in their precise order, given shuffled training indices.
The problem I have is that I cannot retrieve reliable results with my data on my first search. I have to run the search **twice** to get the right answer.
I am indexing data t... | {
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"+1",
"@dspoka Please check the following link : https://github.com/thunlp/FewRel\r\nThis link mentions two versions of the datasets. Also, this one seems to be the official link.\r\n\r\nI am assuming this is the correct link and implementing based on the same.",
"Hi @lhoestq,\r\n\r\nThis issue can be closed, I... | 1,611,186,963,000 | 1,615,258,325,000 | 1,615,214,092,000 | NONE | null | ## Adding a Dataset
- **Name:** FewRel
- **Description:** Large-Scale Supervised Few-Shot Relation Classification Dataset
- **Paper:** @inproceedings{han2018fewrel,
title={FewRel:A Large-Scale Supervised Few-Shot Relation Classification Dataset with State-of-the-Art Evaluation},
auth... | {
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"following_url"... | [] | 1,611,181,124,000 | 1,614,594,981,000 | 1,614,594,981,000 | NONE | null | ## Adding a Dataset
- **Name:** *name of the dataset*
- **Description:** *short description of the dataset (or link to social media or blog post)*
- CCAligned consists of parallel or comparable web-document pairs in 137 languages aligned with English. These web-document pairs were constructed by performing language ... | {
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"You can use `Dataset.flatten_indices()` to make it fast after a select or shuffle.",
"Thanks for the input! I gave that a try by adding this after my selection / reordering operations, but before the big computation task of `score_squad`\r\n\r\n```\r\nexamples = examples.flatten_indices()\r\nfeatures = features.... | 1,611,177,132,000 | 1,611,180,219,000 | 1,611,180,219,000 | NONE | null | I am using portions of HF's helpful work in preparing / scoring the SQuAD 2.0 data. The problem I have is that after using `select` to re-ordering the dataset, computations slow down immensely where the total scoring process on 131k training examples would take maybe 3 minutes, now take over an hour.
The below examp... | {
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"following_url"... | [] | 1,611,141,060,000 | 1,611,565,927,000 | 1,611,565,926,000 | MEMBER | null | As noticed by @JetRunner there was some issues when trying to generate a dataset using a custom config that is based on an existing config.
For example in the following code the `mnli_custom` would reuse the cache used to create `mnli` instead of generating a new dataset with the new label classes:
```python
from ... | {
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"following_url"... | [] | 1,611,139,958,000 | 1,611,153,570,000 | 1,611,153,570,000 | CONTRIBUTOR | null | I realized COMET citations were not showing in the hugging face metrics page:
<img width="814" alt="Screenshot 2021-01-20 at 09 48 44" src="https://user-images.githubusercontent.com/17256847/105164848-8b9da900-5b0d-11eb-9e20-a38f559d2037.png">
This pull request is intended to fix that.
Thanks! | {
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"I think its better to create a new branch with this fix. I forgot I was still using the old branch."
] | 1,611,136,483,000 | 1,611,138,427,000 | 1,611,138,302,000 | CONTRIBUTOR | null | In my last pull request to add COMET metric, the citations where not following the usual "format". Because of that they where not correctly displayed on the website:
<img width="814" alt="Screenshot 2021-01-20 at 09 48 44" src="https://user-images.githubusercontent.com/17256847/105158000-686efb80-5b05-11eb-8bb0-9c8... | {
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"following_url"... | [] | 1,611,078,780,000 | 1,611,154,612,000 | 1,611,154,612,000 | CONTRIBUTOR | null | See the updated card at https://github.com/mcmillanmajora/datasets/tree/add-SBIC-card/datasets/social_bias_frames. I incorporated information from the [SBIC data statement](https://homes.cs.washington.edu/~msap/social-bias-frames/DATASTATEMENT.html), paper, and the corpus README file included with the dataset download. | {
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https://api.github.com/repos/huggingface/datasets/issues/1750 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1750/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1750/comments | https://api.github.com/repos/huggingface/datasets/issues/1750/events | https://github.com/huggingface/datasets/pull/1750 | 788,668,085 | MDExOlB1bGxSZXF1ZXN0NTU3MTM1MzM1 | 1,750 | Fix typo in README.md of cnn_dailymail | {
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"Good catch, thanks!",
"Thank you for merging!"
] | 1,611,025,565,000 | 1,611,054,449,000 | 1,611,049,723,000 | CONTRIBUTOR | null | When I read the README.md of `CNN/DailyMail Dataset`, there seems to be a typo `CCN`.
I am afraid this is a trivial matter, but I would like to make a suggestion for revision. | {
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"I will push updates tomorrow.",
"@lhoestq thank you for your comments! I went ahead and fixed the code 😃. Please let me know if I missed anything."
] | 1,610,994,992,000 | 1,611,948,952,000 | 1,611,945,488,000 | CONTRIBUTOR | null | Switchboard Dialog Act Corpus
I made some changes following @bhavitvyamalik recommendation in #1678:
* Contains all metadata.
* Used official implementation from the [/swda](https://github.com/cgpotts/swda) repo.
* Add official train and test splits used in [Stolcke et al. (2000)](https://web.stanford.edu/~jur... | {
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"Hi :) \r\nThe slicing API from https://huggingface.co/docs/datasets/splits.html doesn't shuffle the data.\r\nYou can shuffle and then take a subset of your dataset with\r\n```python\r\n# shuffle and take the first 100 examples\r\ndataset = dataset.shuffle(seed=42).select(range(100))\r\n```\r\n\r\nYou can find more... | 1,610,978,935,000 | 1,610,981,134,000 | null | NONE | null | Hi
I need to slice a dataset with random seed, I looked into documentation here https://huggingface.co/docs/datasets/splits.html
I could not find a seed option, could you assist me please how I can get a slice for different seeds?
thank you.
@lhoestq | {
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"From the description given in the dataset script for `wsc.fixed`:\r\n```\r\nThis version fixes issues where the spans are not actually substrings of the text.\r\n```"
] | 1,610,931,019,000 | 1,610,967,763,000 | 1,610,931,574,000 | NONE | null | Hi
I see two versions of wsc in superglue, and I am not sure what is the differences and which one is the original one. could you help to discuss the differences? thanks @lhoestq | {
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"@lhoestq I ran `make style` but CI code quality still failing and I don't have access to logs",
"It's also likely that due to the previous placement of the field initialization, much of the data about topics etc was simply wrong and carried over from previous entries. Model scores seem to improve significantly w... | 1,610,870,329,000 | 1,610,969,169,000 | 1,610,969,169,000 | CONTRIBUTOR | null | This brings the number of examples for ModApte to match the stated `Training set (9,603 docs)...Test Set (3,299 docs)` | {
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"Currently it's only possible to define the features for the two columns `references` and `predictions`.\r\nThe data for these columns can then be passed to `metric.add_batch` and `metric.compute`.\r\nInstead of defining more columns `text`, `offset_mapping` and `ground` you must include them in either references a... | 1,610,866,874,000 | 1,611,333,900,000 | null | CONTRIBUTOR | null | Hi Team,
I am trying to create a custom metric for my training as follows, where f1 is my own metric:
```python
def _info(self):
# TODO: Specifies the datasets.MetricInfo object
return datasets.MetricInfo(
# This is the description that will appear on the metrics page.
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"Maybe it would be simpler to just overwrite the order of the label classes of the `glue` dataset ?\r\n```python\r\nmnli = load_dataset(\"glue\", \"mnli\", label_classes=[\"contradiction\", \"entailment\", \"neutral\"])\r\n```",
"Sounds good. Will close the issue if that works."
] | 1,610,862,865,000 | 1,617,021,810,000 | 1,617,021,810,000 | MEMBER | null | Link to our discussion on Slack (HF internal)
https://huggingface.slack.com/archives/C014N4749J9/p1609668119337400
The next step is to add a compatible option in the new `run_glue.py`
I duplicated `glue` and made the following changes:
1. Change the name to `glue_compat`.
2. Change the label assignments for MN... | {
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] | 1,610,763,799,000 | 1,610,764,768,000 | 1,610,764,758,000 | NONE | null | dataset:sem_eval_2014_task_1
pretrained_model:bert-base-uncased
error description:
when i use these resoruce to train fine_tuning a text_classification on sem_eval_2014_task_1,there always be some problem(when i use other dataset ,there exist the error too). And i followed the colab code (url:https://colab.researc... | {
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"following_url"... | [] | 1,610,751,514,000 | 1,611,150,086,000 | 1,611,150,086,000 | CONTRIBUTOR | null | id_liputan6 is a large-scale Indonesian summarization dataset. The articles were harvested from an online news portal, and obtain 215,827 document-summary pairs: https://arxiv.org/abs/2011.00679 | {
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"The dataset card is fantastic!\r\n\r\nLooks good to me! Did you check that this still passes the slow tests with the existing dummy data?",
"Yes, I ran and passed all the tests specified in [this guide](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md#automatically-add-code-metadata), inclu... | 1,610,747,123,000 | 1,611,930,846,000 | 1,611,917,583,000 | CONTRIBUTOR | null | - fixes test sets loading in v3.0
- adds additional fields for v3.0_ru
- adds info to the WebNLG data card | {
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"Nice thanks :) \r\nNote that in `datasets` the tags are simply the version without the `v`. For example `1.2.1`.",
"Do you push tags only for versions?",
"Yes I've always used tags only for versions"
] | 1,610,637,085,000 | 1,610,705,300,000 | 1,610,705,299,000 | MEMBER | null | Will push a new version on anaconda cloud every time a tag starting with `v` is pushed (like `v1.2.2`).
Will appear here: https://anaconda.org/huggingface/datasets
Depends on `conda-forge` for now, so the following is required for installation:
```
conda install -c huggingface -c conda-forge datasets
``` | {
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"Thanks for updating this!"
] | 1,610,592,561,000 | 1,610,619,924,000 | 1,610,619,924,000 | CONTRIBUTOR | null | Base on this issue https://github.com/huggingface/datasets/issues/1064, I can now use the official links.
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"following_url"... | [] | 1,610,570,344,000 | 1,610,620,178,000 | 1,610,620,178,000 | CONTRIBUTOR | null | I added this dataset some days ago, and today I used it to train some models and realized that the names of the features aren't so good.
Looking at the current features hierarchy, we have "paragraphs" with a list of "sentences" with a list of "sentences?!". But the actual hierarchy is a "text" with a list of "paragr... | {
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"Add new \"dataset\"? ;)",
"Lol, too used to Transformers ;-)"
] | 1,610,550,489,000 | 1,610,637,361,000 | 1,610,637,360,000 | MEMBER | null | This PR fixes a few typos in the "Add new dataset template" and clarifies a bit what to do for the dummy data creation when the `auto_generate` flag can't work. | {
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https://api.github.com/repos/huggingface/datasets/issues/1733 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1733/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1733/comments | https://api.github.com/repos/huggingface/datasets/issues/1733/events | https://github.com/huggingface/datasets/issues/1733 | 784,903,002 | MDU6SXNzdWU3ODQ5MDMwMDI= | 1,733 | connection issue with glue, what is the data url for glue? | {
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"Hello @juliahane, which config of GLUE causes you trouble?\r\nThe URLs are defined in the dataset script source code: https://github.com/huggingface/datasets/blob/master/datasets/glue/glue.py"
] | 1,610,527,060,000 | 1,628,100,835,000 | 1,628,100,835,000 | NONE | null | Hi
my codes sometimes fails due to connection issue with glue, could you tell me how I can have the URL datasets library is trying to read GLUE from to test the machines I am working on if there is an issue on my side or not
thanks | {
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https://api.github.com/repos/huggingface/datasets/issues/1732 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1732/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1732/comments | https://api.github.com/repos/huggingface/datasets/issues/1732/events | https://github.com/huggingface/datasets/pull/1732 | 784,874,490 | MDExOlB1bGxSZXF1ZXN0NTUzOTkzNTAx | 1,732 | [GEM Dataset] Added TurkCorpus, an evaluation dataset for sentence simplification. | {
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"Thank you for the feedback! I updated the code. "
] | 1,610,524,219,000 | 1,610,619,581,000 | 1,610,619,581,000 | CONTRIBUTOR | null | We want to use TurkCorpus for validation and testing of the sentence simplification task. | {
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"Hi @yangp725,\r\nThe SWDA has been added very recently and has not been released yet, thus it is not available in the `1.2.0` version of 🤗`datasets`.\r\nYou can still access it by installing the latest version of the library (master branch), by following instructions in [this issue](https://github.com/huggingface... | 1,610,506,660,000 | 1,610,536,660,000 | 1,610,536,660,000 | NONE | null | ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/1.2.0/datasets/swda/swda.py
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https://api.github.com/repos/huggingface/datasets/issues/1730 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1730/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1730/comments | https://api.github.com/repos/huggingface/datasets/issues/1730/events | https://github.com/huggingface/datasets/pull/1730 | 784,617,525 | MDExOlB1bGxSZXF1ZXN0NTUzNzgxMDY0 | 1,730 | Add MNIST dataset | {
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https://api.github.com/repos/huggingface/datasets/issues/1729 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1729/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1729/comments | https://api.github.com/repos/huggingface/datasets/issues/1729/events | https://github.com/huggingface/datasets/issues/1729 | 784,565,898 | MDU6SXNzdWU3ODQ1NjU4OTg= | 1,729 | Is there support for Deep learning datasets? | {
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"Hi @ZurMaD!\r\nThanks for your interest in 🤗 `datasets`. Support for image datasets is at an early stage, with CIFAR-10 added in #1617 \r\nMNIST is also on the way: #1730 \r\n\r\nIf you feel like adding another image dataset, I would advise starting by reading the [ADD_NEW_DATASET.md](https://github.com/huggingfa... | 1,610,482,961,000 | 1,617,164,647,000 | 1,617,164,647,000 | NONE | null | I looked around this repository and looking the datasets I think that there's no support for images-datasets. Or am I missing something? For example to add a repo like this https://github.com/DZPeru/fish-datasets | {
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https://api.github.com/repos/huggingface/datasets/issues/1728 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1728/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1728/comments | https://api.github.com/repos/huggingface/datasets/issues/1728/events | https://github.com/huggingface/datasets/issues/1728 | 784,458,342 | MDU6SXNzdWU3ODQ0NTgzNDI= | 1,728 | Add an entry to an arrow dataset | {
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"Hi @ameet-1997,\r\nI think what you are looking for is the `concatenate_datasets` function: https://huggingface.co/docs/datasets/processing.html?highlight=concatenate#concatenate-several-datasets\r\n\r\nFor your use case, I would use the [`map` method](https://huggingface.co/docs/datasets/processing.html?highlight... | 1,610,474,507,000 | 1,610,997,332,000 | 1,610,997,332,000 | NONE | null | Is it possible to add an entry to a dataset object?
**Motivation: I want to transform the sentences in the dataset and add them to the original dataset**
For example, say we have the following code:
``` python
from datasets import load_dataset
# Load a dataset and print the first examples in the training s... | {
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https://api.github.com/repos/huggingface/datasets/issues/1727 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1727/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1727/comments | https://api.github.com/repos/huggingface/datasets/issues/1727/events | https://github.com/huggingface/datasets/issues/1727 | 784,435,131 | MDU6SXNzdWU3ODQ0MzUxMzE= | 1,727 | BLEURT score calculation raises UnrecognizedFlagError | {
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"Upgrading tensorflow to version 2.4.0 solved the issue.",
"I still have the same error even with TF 2.4.0.",
"And I have the same error with TF 2.4.1. I believe this issue should be reopened. Any ideas?!",
"I'm seeing the same issue with TF 2.4.1 when running the following in https://colab.research.google.co... | 1,610,472,422,000 | 1,618,266,101,000 | null | NONE | null | Calling the `compute` method for **bleurt** metric fails with an `UnrecognizedFlagError` for `FLAGS.bleurt_batch_size`.
My environment:
```
python==3.8.5
datasets==1.2.0
tensorflow==2.3.1
cudatoolkit==11.0.221
```
Test code for reproducing the error:
```
from datasets import load_metric
bleurt = load_me... | {
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https://api.github.com/repos/huggingface/datasets/issues/1726 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1726/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1726/comments | https://api.github.com/repos/huggingface/datasets/issues/1726/events | https://github.com/huggingface/datasets/pull/1726 | 784,336,370 | MDExOlB1bGxSZXF1ZXN0NTUzNTQ0ODg4 | 1,726 | Offline loading | {
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"It's maybe a bit annoying to add but could we maybe have as well a version of the local data loading scripts in the package?\r\nThe `text`, `json`, `csv`. Thinking about people like in #1725 who are expecting to be able to work with local data without downloading anything.\r\n\r\nMaybe we can add them to package_d... | 1,610,464,917,000 | 1,644,921,130,000 | 1,611,074,552,000 | MEMBER | null | As discussed in #824 it would be cool to make the library work in offline mode.
Currently if there's not internet connection then modules (datasets or metrics) that have already been loaded in the past can't be loaded and it raises a ConnectionError.
This is because `prepare_module` fetches online for the latest vers... | {
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https://api.github.com/repos/huggingface/datasets/issues/1725 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1725/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1725/comments | https://api.github.com/repos/huggingface/datasets/issues/1725/events | https://github.com/huggingface/datasets/issues/1725 | 784,182,273 | MDU6SXNzdWU3ODQxODIyNzM= | 1,725 | load the local dataset | {
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"You should rephrase your question or give more examples and details on what you want to do.\r\n\r\nit’s not possible to understand it and help you with only this information.",
"sorry for that.\r\ni want to know how could i load the train set and the test set from the local ,which api or function should i use .\... | 1,610,453,575,000 | 1,614,768,943,000 | null | NONE | null | your guidebook's example is like
>>>from datasets import load_dataset
>>> dataset = load_dataset('json', data_files='my_file.json')
but the first arg is path...
so how should i do if i want to load the local dataset for model training?
i will be grateful if you can help me handle this problem!
thanks a lot! | {
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https://api.github.com/repos/huggingface/datasets/issues/1723 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1723/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1723/comments | https://api.github.com/repos/huggingface/datasets/issues/1723/events | https://github.com/huggingface/datasets/pull/1723 | 783,982,100 | MDExOlB1bGxSZXF1ZXN0NTUzMjQ4MzU1 | 1,723 | ADD S3 support for downloading and uploading processed datasets | {
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"I created the documentation for `FileSystem Integration for cloud storage` with loading and saving datasets to/from a filesystem with an example of using `datasets.filesystem.S3Filesystem`. I added a note on the `Saving a processed dataset on disk and reload` saying that it is also possible to use other filesystem... | 1,610,435,854,000 | 1,611,680,528,000 | 1,611,680,528,000 | MEMBER | null | # What does this PR do?
This PR adds the functionality to load and save `datasets` from and to s3.
You can save `datasets` with either `Dataset.save_to_disk()` or `DatasetDict.save_to_disk`.
You can load `datasets` with either `load_from_disk` or `Dataset.load_from_disk()`, `DatasetDict.load_from_disk()`.
Lo... | {
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https://api.github.com/repos/huggingface/datasets/issues/1724 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1724/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1724/comments | https://api.github.com/repos/huggingface/datasets/issues/1724/events | https://github.com/huggingface/datasets/issues/1724 | 784,023,338 | MDU6SXNzdWU3ODQwMjMzMzg= | 1,724 | could not run models on a offline server successfully | {
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"Transferred to `datasets` based on the stack trace.",
"Hi @lkcao !\r\nYour issue is indeed related to `datasets`. In addition to installing the package manually, you will need to download the `text.py` script on your server. You'll find it (under `datasets/datasets/text`: https://github.com/huggingface/datasets/... | 1,610,431,686,000 | 1,614,785,549,000 | null | NONE | null | Hi, I really need your help about this.
I am trying to fine-tuning a RoBERTa on a remote server, which is strictly banning internet. I try to install all the packages by hand and try to run run_mlm.py on the server. It works well on colab, but when I try to run it on this offline server, it shows:
![image](https://us... | {
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https://api.github.com/repos/huggingface/datasets/issues/1722 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1722/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1722/comments | https://api.github.com/repos/huggingface/datasets/issues/1722/events | https://github.com/huggingface/datasets/pull/1722 | 783,921,679 | MDExOlB1bGxSZXF1ZXN0NTUzMTk3MTg4 | 1,722 | Added unfiltered versions of the Wiki-Auto training data for the GEM simplification task. | {
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"The current version of Wiki-Auto dataset contains a filtered version of the aligned dataset. The commit adds unfiltered versions of the data that can be useful the GEM task participants."
] | 1,610,429,164,000 | 1,610,475,293,000 | 1,610,472,957,000 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/datasets/issues/1721 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1721/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1721/comments | https://api.github.com/repos/huggingface/datasets/issues/1721/events | https://github.com/huggingface/datasets/pull/1721 | 783,828,428 | MDExOlB1bGxSZXF1ZXN0NTUzMTIyODQ5 | 1,721 | [Scientific papers] Mirror datasets zip | {
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"> Nice !\r\n> \r\n> Could you try to reduce the size of the dummy_data.zip files ? they're quite big (300KB)\r\n\r\nYes, I think it might make sense to enhance the tool a tiny bit to prevent this automatically",
"That's the lightest I can make it...it's long-range summarization so a single sample has ~11000 toke... | 1,610,414,140,000 | 1,610,452,155,000 | 1,610,451,707,000 | MEMBER | null | Datasets were uploading to https://s3.amazonaws.com/datasets.huggingface.co/scientific_papers/1.1.1/arxiv-dataset.zip and https://s3.amazonaws.com/datasets.huggingface.co/scientific_papers/1.1.1/pubmed-dataset.zip respectively to escape google drive quota and enable faster download. | {
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https://api.github.com/repos/huggingface/datasets/issues/1720 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1720/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1720/comments | https://api.github.com/repos/huggingface/datasets/issues/1720/events | https://github.com/huggingface/datasets/pull/1720 | 783,721,833 | MDExOlB1bGxSZXF1ZXN0NTUzMDM0MzYx | 1,720 | Adding the NorNE dataset for NER | {
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"Quick question, @lhoestq. In this specific dataset, two special types `GPE_LOC` and `GPE_ORG` can easily be altered depending on the task, choosing either the more general `GPE` tag or the more specific `LOC`/`ORG` tags, conflating them with the other annotations of the same type. However, I have not found an easy... | 1,610,400,853,000 | 1,617,200,629,000 | 1,617,199,997,000 | CONTRIBUTOR | null | NorNE is a manually annotated corpus of named entities which extends the annotation of the existing Norwegian Dependency Treebank. Comprising both of the official standards of written Norwegian (Bokmål and Nynorsk), the corpus contains around 600,000 tokens and annotates a rich set of entity types including persons, or... | {
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https://api.github.com/repos/huggingface/datasets/issues/1719 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1719/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1719/comments | https://api.github.com/repos/huggingface/datasets/issues/1719/events | https://github.com/huggingface/datasets/pull/1719 | 783,557,542 | MDExOlB1bGxSZXF1ZXN0NTUyODk3MzY4 | 1,719 | Fix column list comparison in transmit format | {
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This is because of an issue in `transmit_format` where the column list comparison fails because the order was not deterministic. This causes the `transmit_format` to apply an unnecessary `set_format` transform with shuffled col... | {
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"Thanks for reporting !\r\nI was able to reproduce thanks to your code and find the origin of the bug.\r\nThe cache was not reusing the same file because one object was not deterministic. It comes from a conversion from `set` to `list` in the `datasets.arrrow_dataset.transmit_format` function, where the resulting l... | 1,610,379,451,000 | 1,619,591,723,000 | 1,611,629,279,000 | NONE | null | Hi,
I am using the datasets package and even though I run the same data processing functions, datasets always recomputes the function instead of using cache.
I have attached an example script that for me reproduces the problem.
In the attached example the second map function always recomputes instead of loading fr... | {
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"Hi Dave,\r\nYou are more than welcome to open a PR to make these changes! 🤗\r\nYou will find the relevant information about opening a PR in the [contributing guide](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md) and in the [dataset addition guide](https://github.com/huggingface/datasets/blob... | 1,610,342,800,000 | 1,611,629,537,000 | 1,611,629,537,000 | CONTRIBUTOR | null | Hi,
SciFact dataset creator here. First of all, thanks for adding the dataset to Huggingface, much appreciated!
I'd like to make a few minor changes, including the citation information and the `_URL` from which to download the dataset. Can I submit a PR for this?
It also looks like the dataset is being downloa... | {
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"Oh that's a really cool one, we'll review/merge it soon!\r\n\r\nIn the meantime, do you have any specific positive/negative feedback on the process of adding a datasets Max?\r\nDid you follow the instruction in the [detailed step-by-step](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md)?",
... | 1,610,142,369,000 | 1,610,553,924,000 | 1,610,553,924,000 | CONTRIBUTOR | null | Adding the adversarialQA dataset (https://adversarialqa.github.io/) from Beat the AI (https://arxiv.org/abs/2002.00293) | {
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"Yes indeed the idea is to have the next release on conda cc @LysandreJik ",
"Great! Did you guys have a timeframe in mind for the next release?\r\n\r\nThank you for all the great work in developing this library.",
"I think we can have `datasets` on conda by next week. Will see what I can do!",
"Thank you. Lo... | 1,610,133,135,000 | 1,631,882,860,000 | 1,631,882,860,000 | NONE | null | Will a conda package for installing datasets be added to the huggingface conda channel? I have installed transformers using conda and would like to use the datasets library to use some of the scripts in the transformers/examples folder but am unable to do so at the moment as datasets can only be installed using pip and... | {
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"When should we expect to see our dataset appear in the search dropdown at huggingface.co?",
"Hi @eusip,\r\n\r\n> When should we expect to see our dataset appear in the search dropdown at huggingface.co?\r\n\r\nwhen this PR is merged.",
"Thanks!",
"I've implemented all the changes requested by @lhoestq but I ... | 1,610,130,258,000 | 1,611,238,357,000 | 1,611,225,071,000 | CONTRIBUTOR | null | My collaborators and I within the Affective Computing team at Telecom Paris would like to push our spoken dialogue dataset for publication. | {
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"following_url"... | [] | 1,610,113,556,000 | 1,610,357,000,000 | 1,610,356,999,000 | MEMBER | null | As noticed in #807 there's currently an issue with `cached_path` not raising `FileNotFoundError` on windows for absolute paths. This is due to the way we check for a path to be local or not. The check on the scheme using urlparse was incomplete.
I fixed this and added tests | {
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"I haven't tested C4 on my side so there so there may be a few bugs in the code/adjustments to make.\r\nHere it looks like in c4.py, line 190 one of the `files_to_download` is `'/'` which is invalid.\r\nValid files are paths to local files or URLs to remote files."
] | 1,610,091,090,000 | 1,610,531,053,000 | null | NONE | null | **TLDR**:
I fail to download C4 and see a stacktrace originating in `IsADirectoryError` as an explanation for failure.
How can the problem be fixed?
**VERBOSE**:
I use Python version 3.7 and have the following dependencies listed in my project:
```
datasets==1.2.0
apache-beam==2.26.0
```
When runn... | {
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"following_url"... | [] | 1,610,086,443,000 | 1,610,096,408,000 | 1,610,096,408,000 | NONE | null | ## Adding a Dataset
- **Name:** *name of the dataset*
- **Description:** *short description of the dataset (or link to social media or blog post)*
- **Paper:** *link to the dataset paper if available*
- **Data:** *link to the Github repository or current dataset location*
- **Motivation:** *what are some good reasons t... | {
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- **Name:** *name of the dataset*
- **Description:** *short description of the dataset (or link to social media or blog post)*
- **Paper:** *link to the dataset paper if available*
- **Data:** *link to the Github repository or current dataset location*
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"Looks like we need to trim the ones with too many configs, will look into it tomorrow!"
] | 1,610,043,006,000 | 1,610,980,353,000 | 1,610,980,353,000 | CONTRIBUTOR | null | This is it: we worked on a generator with Yacine @yjernite , and we generated dataset cards for all missing ones (161), with all the information we could gather from datasets repository, and using dummy_data to generate examples when possible.
Code is available here for the moment: https://github.com/madlag/datasets... | {
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"Hi ! Is this an issue you have with `openwebtext` specifically or also with other datasets ?\r\n\r\nIt looks like the downloaded file is corrupted and can't be extracted using `tarfile`.\r\nCould you try loading it again with \r\n```python\r\nimport datasets\r\ndatasets.load_dataset(\"openwebtext\", download_mode=... | 1,610,041,695,000 | 1,610,534,102,000 | null | CONTRIBUTOR | null | I receive the following error after about an hour trying to download the `openwebtext` dataset.
The code used is:
```python
import datasets
datasets.load_dataset("openwebtext")
```
> Traceback (most recent call last): ... | {
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"following_url"... | [] | 1,610,039,924,000 | 1,610,460,481,000 | 1,610,460,481,000 | CONTRIBUTOR | null | Related to #215.
Missing improvements from @lhoestq's #1703. | {
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"I few comments here for discussion:\r\n- I'm not convinced yet the end user should really have to understand the difference between \"caching\" and 'fingerprinting\", what do you think? I think fingerprinting should probably stay as an internal thing. Is there a case where we want cahing without fingerprinting or ... | 1,610,033,189,000 | 1,611,077,531,000 | 1,611,077,530,000 | MEMBER | null | This PR adds these features:
- Enable/disable caching
If disabled, the library will no longer reload cached datasets files when applying transforms to the datasets.
It is equivalent to setting `load_from_cache` to `False` in dataset transforms.
```python
from datasets import set_caching_enabled
set_cach... | {
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https://api.github.com/repos/huggingface/datasets/issues/1701 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1701/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1701/comments | https://api.github.com/repos/huggingface/datasets/issues/1701/events | https://github.com/huggingface/datasets/issues/1701 | 781,345,717 | MDU6SXNzdWU3ODEzNDU3MTc= | 1,701 | Some datasets miss dataset_infos.json or dummy_data.zip | {
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"Thanks for reporting.\r\nWe should indeed add all the missing dummy_data.zip and also the dataset_infos.json at least for lm1b, reclor and wikihow.\r\n\r\nFor c4 I haven't tested the script and I think we'll require some optimizations regarding beam datasets before processing it.\r\n"
] | 1,610,029,033,000 | 1,610,458,846,000 | null | CONTRIBUTOR | null | While working on dataset REAME generation script at https://github.com/madlag/datasets_readme_generator , I noticed that some datasets miss a dataset_infos.json :
```
c4
lm1b
reclor
wikihow
```
And some does not have a dummy_data.zip :
```
kor_nli
math_dataset
mlqa
ms_marco
newsgroup
qa4mre
qanga... | {
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https://api.github.com/repos/huggingface/datasets/issues/1700 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1700/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1700/comments | https://api.github.com/repos/huggingface/datasets/issues/1700/events | https://github.com/huggingface/datasets/pull/1700 | 781,333,589 | MDExOlB1bGxSZXF1ZXN0NTUxMDc1NTg2 | 1,700 | Update Curiosity dialogs DatasetCard | {
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There are some entries in the data fields section yet to be filled. There is little information regarding those fields. | {
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https://api.github.com/repos/huggingface/datasets/issues/1699 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1699/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1699/comments | https://api.github.com/repos/huggingface/datasets/issues/1699/events | https://github.com/huggingface/datasets/pull/1699 | 781,271,558 | MDExOlB1bGxSZXF1ZXN0NTUxMDIzODE5 | 1,699 | Update DBRD dataset card and download URL | {
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"not sure why the CI was not triggered though"
] | 1,610,021,803,000 | 1,610,026,899,000 | 1,610,026,859,000 | CONTRIBUTOR | null | I've added the Dutch Bood Review Dataset (DBRD) during the recent sprint. This pull request makes two minor changes:
1. I'm changing the download URL from Google Drive to the dataset's GitHub release package. This is now possible because of PR #1316.
2. I've updated the dataset card.
Cheers! 😄 | {
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