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It should fix the CI that is currently failing. | {
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- Citation: Replace preprint with proceedings
- URL: Use a URL with long-term availability
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I would appreciate if you could help me with this issue. | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/289... | This PR makes the following update to the xsum dataset:
- Manual download is not required anymore
- dataset can be loaded as follow: `nlp.load_dataset('xsum')`
**Important**
Instead of using on outdated url to download the data: "https://raw.githubusercontent.com/EdinburghNLP/XSum/master/XSum-Dataset/XSum... | {
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_np_qint8 = np.dtype([("qint8", np.int8, 1)])
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The imports were wrong | {
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Some datasets like XTREME and all WMT need the manual data dir only for a small fraction of the possible configs.
After some brainstorming with @mariamabarham and @lhoestq... | {
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Can we make it so that they all are proper citations, i.e. parse by the bibtex spec:
https://bibtexparser.readthedocs.io/en/master/ | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/282... | Some datasets are hosted on gcs (wikipedia for example). In this PR I make sure that, when a user loads such datasets, the file_instructions are built using the dataset_info.json from gcs and not from the info extracted from the local `dataset_infos.json` (the one that contain the info for each config). Indeed local fi... | {
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https://api.github.com/repos/huggingface/datasets/issues/281 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/281/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/281/comments | https://api.github.com/repos/huggingface/datasets/issues/281/events | https://github.com/huggingface/datasets/issues/281 | 641,067,856 | MDU6SXNzdWU2NDEwNjc4NTY= | 281 | Private/sensitive data | {
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Thanks for this fantastic library, it makes it very easy to do prototyping for NLP projects interchangeably between TF/Pytorch.
Unfortunately, there is data that cannot easily be shared publicly as it may contain sensitive information.
Is there support/a plan to support such data with NLP, e.g. by readin... | {
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https://api.github.com/repos/huggingface/datasets/issues/280 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/280/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/280/comments | https://api.github.com/repos/huggingface/datasets/issues/280/events | https://github.com/huggingface/datasets/issues/280 | 640,677,615 | MDU6SXNzdWU2NDA2Nzc2MTU= | 280 | Error with SquadV2 Metrics | {
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**squad_metric = nlp.load_metric('squad_v2')**
**This throws me an error.:**
```
ImportError Traceback (most recent call last)
<ipython-input-8-170b6a170555> in <module>
----> 1 squad_metric = nlp.load_metric('squad_v2')
~/env/lib6... | {
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https://api.github.com/repos/huggingface/datasets/issues/279 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/279/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/279/comments | https://api.github.com/repos/huggingface/datasets/issues/279/events | https://github.com/huggingface/datasets/issues/279 | 640,611,692 | MDU6SXNzdWU2NDA2MTE2OTI= | 279 | Dataset Preprocessing Cache with .map() function not working as expected | {
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Is there a way to disable using the cache when processing a dataset? As I make minor processing changes on the same dataset, I ... | {
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https://api.github.com/repos/huggingface/datasets/issues/278 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/278/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/278/comments | https://api.github.com/repos/huggingface/datasets/issues/278/events | https://github.com/huggingface/datasets/issues/278 | 640,518,917 | MDU6SXNzdWU2NDA1MTg5MTc= | 278 | MemoryError when loading German Wikipedia | {
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I'm trying to download the German Wikipedia dataset as follows:
```
wiki = nlp.load_dataset("wikip... | {
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https://api.github.com/repos/huggingface/datasets/issues/277 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/277/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/277/comments | https://api.github.com/repos/huggingface/datasets/issues/277/events | https://github.com/huggingface/datasets/issues/277 | 640,163,053 | MDU6SXNzdWU2NDAxNjMwNTM= | 277 | Empty samples in glue/qqp | {
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qqp = nlp.load_dataset('glue', 'qqp')
print(qqp['train'][310121])
print(qqp['train'][362225])
```
```
{'question1': 'How can I create an Android app?', 'question2': '', 'label': 0, 'idx': 310137}
{'question1': 'How can I develop android app?', 'question2': '', 'label': 0, 'idx': 362246}
```
Notice that que... | {
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However metrics load data the same way but don't need instructions (we use one single file).
In this PR I just make `original_instructions` optional when reading files to load a `Datas... | {
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The error is:
```
---------------------------------------------------------------------------
NonMatchingChecksumError Traceback (most recent call last)
<ipython-input-2-7742dea167d0> in <module... | {
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I was wondering if you would be open to adding PG-19 to your collection of datasets. https://github.com/deepmind/pg19 It is often used for benchmarking long-range language modeling. | {
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@nazneenrajani | {
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} | This is a patch for #244. According to the [live nlp viewer](url), the Allociné dataset must be loaded with :
```python
dataset = load_dataset('allocine', 'allocine')
```
This is redundant, as there is only one "dataset configuration", and should only be:
```python
dataset = load_dataset('allocine')
```
This ... | {
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```python
ModuleNotFoundError: No module named 'langdetect'
Traceback:
File "/home/sasha/.local/lib/python3.7/site-packages/streamlit/ScriptRunner.py", line 322, in _run_script
exec(code, module.__d... | {
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https://api.github.com/repos/huggingface/datasets/issues/269 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/269/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/269/comments | https://api.github.com/repos/huggingface/datasets/issues/269/events | https://github.com/huggingface/datasets/issues/269 | 638,106,774 | MDU6SXNzdWU2MzgxMDY3NzQ= | 269 | Error in metric.compute: missing `original_instructions` argument | {
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"gists... | null | [] | 2020-06-13T06:26:54Z | 2020-06-18T07:41:44Z | 2020-06-18T07:41:44Z | NONE | null | null | null | I'm running into an error using metrics for computation in the latest master as well as version 0.2.1. Here is a minimal example:
```python
import nlp
rte_metric = nlp.load_metric('glue', name="rte")
rte_metric.compute(
[0, 0, 1, 1],
[0, 1, 0, 1],
)
```
```
181 # Read the predictio... | {
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https://api.github.com/repos/huggingface/datasets/issues/267 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/267/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/267/comments | https://api.github.com/repos/huggingface/datasets/issues/267/events | https://github.com/huggingface/datasets/issues/267 | 637,415,545 | MDU6SXNzdWU2Mzc0MTU1NDU= | 267 | How can I load/find WMT en-romanian? | {
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When I run
```python
wmt = nlp.load_dataset('wmt16')
```
I get:
```python
AssertionError: The dataset wmt16 with config cs-en requires manual data.
Please follow the manual download instructions: Some of the wmt configs here, require a manual download.
Please look into wm... | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/266... | Add a bunch of methods to reorder/split/select rows in a dataset:
- `dataset.select(indices)`: Create a new dataset with rows selected following the list/array of indices (which can have a different size than the dataset and contain duplicated indices, the only constrain is that all the integers in the list must be sm... | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/265... | When a user installs `nlp` on google colab, then google colab doesn't update pyarrow, and the runtime needs to be restarted to use the updated version of pyarrow.
This is an issue because `nlp` requires the updated version to work correctly.
In this PR I added en error that is shown to the user in google colab if... | {
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https://api.github.com/repos/huggingface/datasets/issues/264 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/264/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/264/comments | https://api.github.com/repos/huggingface/datasets/issues/264/events | https://github.com/huggingface/datasets/pull/264 | 637,106,170 | MDExOlB1bGxSZXF1ZXN0NDMzMTU0ODQ4 | 264 | Fix small issues creating dataset | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/264... | Fix many small issues mentioned in #249:
- don't force to install apache beam for commands
- fix None cache dir when using `dl_manager.download_custom`
- added new extras in `setup.py` named `dev` that contains tests and quality dependencies
- mock dataset sizes when running tests with dummy data
- add a note abou... | {
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In recent years many researchers have advocated that learning meanings from text-based only datasets is just like asking a human to "learn to speak by listening to the radio" [[E. Bender and A. Koller,2020](https://openreview.net/forum?id=GKTvAcb12b), [Y. Bisk et. al, 2020](https://arxiv.org/abs/2004.10... | {
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https://api.github.com/repos/huggingface/datasets/issues/262 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/262/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/262/comments | https://api.github.com/repos/huggingface/datasets/issues/262/events | https://github.com/huggingface/datasets/pull/262 | 636,702,849 | MDExOlB1bGxSZXF1ZXN0NDMyODI3Mzcz | 262 | Add new dataset ANLI Round 1 | {
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} | Adding new dataset [ANLI](https://github.com/facebookresearch/anli/).
I'm not familiar with how to add new dataset. Let me know if there is any issue. I only include round 1 data here. There will be round 2, round 3 and more in the future with potentially different format. I think it will be better to separate them. | {
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https://api.github.com/repos/huggingface/datasets/issues/261 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/261/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/261/comments | https://api.github.com/repos/huggingface/datasets/issues/261/events | https://github.com/huggingface/datasets/issues/261 | 636,372,380 | MDU6SXNzdWU2MzYzNzIzODA= | 261 | Downloading dataset error with pyarrow.lib.RecordBatch | {
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```
/usr/local/lib/python3.6/dist-packages/nlp/load.py in load_dataset(path, name, version, data_dir, data_files, split, cache_dir, download_config, download_mode, ignore_verifications, save_infos, **config_kwargs)
518 download_mode=... | {
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https://api.github.com/repos/huggingface/datasets/issues/260 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/260/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/260/comments | https://api.github.com/repos/huggingface/datasets/issues/260/events | https://github.com/huggingface/datasets/pull/260 | 636,261,118 | MDExOlB1bGxSZXF1ZXN0NDMyNDY3NDM5 | 260 | Consistency fixes | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/260... | A few bugs I've found while hacking | {
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https://api.github.com/repos/huggingface/datasets/issues/259 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/259/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/259/comments | https://api.github.com/repos/huggingface/datasets/issues/259/events | https://github.com/huggingface/datasets/issues/259 | 636,239,529 | MDU6SXNzdWU2MzYyMzk1Mjk= | 259 | documentation missing how to split a dataset | {
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I know I can do something like this to access a split which is already in the original dataset :
`ds_test = nlp.load_dataset('imdb, split='test') `
But how can I split ds_test into a test and a validation set (without reading the data into m... | {
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https://api.github.com/repos/huggingface/datasets/issues/258 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/258/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/258/comments | https://api.github.com/repos/huggingface/datasets/issues/258/events | https://github.com/huggingface/datasets/issues/258 | 635,859,525 | MDU6SXNzdWU2MzU4NTk1MjU= | 258 | Why is dataset after tokenization far more larger than the orginal one ? | {
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```
def tokenize_tfm(example):
example['input_ids'] = hf_fast_tokenizer.convert_tokens_to_ids(hf_fast_tokenizer.tokenize(example['text']))
return example
wiki = nlp.load_dataset('wikipedia', '20200501.en', cache_dir=cache_dir)['train']
wiki.map(token... | {
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```
dataset = nlp.load_dataset('cos_e')
tokenizer = GPT2TokenizerFast.from_pretrained('gpt2', cache_dir=cache_dir)
for split in datase... | {
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https://api.github.com/repos/huggingface/datasets/issues/256 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/256/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/256/comments | https://api.github.com/repos/huggingface/datasets/issues/256/events | https://github.com/huggingface/datasets/issues/256 | 635,596,295 | MDU6SXNzdWU2MzU1OTYyOTU= | 256 | [Feature request] Add a feature to dataset | {
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But it is a important use case : After applying some preprocessing, some samples might be empty for example. We should be able to remove these samples from the dataset, or at least mark them as `removed` so when iterating the datase... | {
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} | This PR add the Flue dataset as requested in this issue #223 . @lbourdois made a detailed description in that issue.
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I am trying to load the `imdb` dataset with this line:
`dataset = nlp.load_dataset('imdb', data_dir='/A/PATH', cache_dir='/A/PATH')`
but I am getting the following error:
```
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/mounts/Users/cisintern/antmarakis/anaconda3/... | {
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This way it's easier to access `dataset.feature['label']` for instance
Also, add the original split instructions used to create the dataset in `dataset.split`
Ex:
```
from nlp import load_dataset
stsb = load_dataset('glue', name=... | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/250... | There was a line from the original tfds script that was still there and causing issues when loading the c4 script. This one should fix #233 and allow anyone to load the c4 script to generate the dataset | {
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"gists... | null | [] | 2020-06-07T12:58:54Z | 2020-06-12T08:28:51Z | 2020-06-12T08:28:51Z | CONTRIBUTOR | null | null | null | Hi, I successfully created a dataset and has made a pr #248.
But I have encountered several problems when I was creating it, and those should be easy to fix.
1. Not found dataset_info.json
should be fixed by #241 , eager to wait it be merged.
2. Forced to install `apach_beam`
If we should install it, then it m... | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/248... | 1. I knew there is a branch `toronto_books_corpus`
- After I downloaded it, I found it is all non-english, and only have one row.
- It seems that it cites the wrong paper
- according to papar using it, it is called `BooksCorpus` but not `TornotoBooksCorpus`
2. It use a text mirror in google drive
- `bookscorpu... | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/247... | This PR makes all datasets loading deterministic by applying `sorted()` to all `glob.glob` and `os.listdir` statements.
Are there other "non-deterministic" functions apart from `glob.glob()` and `os.listdir()` that you can think of @thomwolf @lhoestq @mariamabarham @jplu ?
**Important**
It does break backward c... | {
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https://api.github.com/repos/huggingface/datasets/issues/246 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/246/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/246/comments | https://api.github.com/repos/huggingface/datasets/issues/246/events | https://github.com/huggingface/datasets/issues/246 | 632,380,054 | MDU6SXNzdWU2MzIzODAwNTQ= | 246 | What is the best way to cache a dataset? | {
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```
@st.cache
def load_data():
return nlp.load_dataset('squad')
```
This code raises the error "uncachable object"
Right now I just fixed with a constant for my specific case:
```
@st.cache(hash_funcs={pyarrow.lib.Buffer: lambda b: 0})
```... | {
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```
>>> import nlp
>>> glue = nlp.load_dataset('glue', 'sst2')
>>> glue
{'train': Dataset(schema: {'sentence': 'string', 'label': 'int64', 'idx': 'int32'}, num_rows: 67349), 'validation': Dataset(schema: {'sentence': 'st... | {
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https://api.github.com/repos/huggingface/datasets/issues/244 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/244/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/244/comments | https://api.github.com/repos/huggingface/datasets/issues/244/events | https://github.com/huggingface/datasets/pull/244 | 631,869,155 | MDExOlB1bGxSZXF1ZXN0NDI4NjgxMTcx | 244 | Add Allociné Dataset | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/244... | This is a french binary sentiment classification dataset, which was used to train this model: https://huggingface.co/tblard/tf-allocine.
Basically, it's a french "IMDB" dataset, with more reviews.
More info on [this repo](https://github.com/TheophileBlard/french-sentiment-analysis-with-bert). | {
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This makes the GLUE-MNLI dataset readable on my machine, not sure if it's a Windows-only bug. | {
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```python
dataset = nlp.load_dataset('glue', 'mnli')
```
I get an encoding error (could it be because I'm using Windows?) :
```python
# Lots of error log lines later...
~\Miniconda3\envs\nlp\lib\site-packages\tqdm\std.py in __iter__(self)
1128 try:
-> 1129 for obj in iterable:... | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/241... | If the cache dir of a dataset is empty, the dataset fails to load and throws a FileNotFounfError. We could end up with empty cache dir because there was a line in the code that created the cache dir without using a temp dir. Using a temp dir is useful as it gets renamed to the real cache dir only if the full process is... | {
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```python
import nlp
dataset = nlp.load_dataset("trivia_qa", split="validation[:1%]")
```
the resulting dataset is not deterministic over different google colabs.
After talking to @thomwolf, I suspect the reason to be the use of `glob.glob` in line:
https://github.com/huggingface/nlp/blob/2e0... | {
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"gists... | null | [] | 2020-06-05T06:15:04Z | 2020-06-07T13:01:04Z | 2020-06-07T13:01:04Z | CONTRIBUTOR | null | null | null | Hi, I am trying to create Toronto Book Corpus. #131
I ran
`~/nlp % python nlp-cli test datasets/bookcorpus --save_infos --all_configs`
but this doesn't create `dataset_info.json` and try to use it
```
INFO:nlp.load:Checking datasets/bookcorpus/bookcorpus.py for additional imports.
INFO:filelock:Lock 1397953257... | {
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> Warning: Empty candidate sentence; Setting recall to be 0.
Code :
```
import nlp
metric = nlp.load_metric("bertscore")
scores = metric.compute(["swag", "swags"], ["swags", "totally something different"], lang="en", device=0)
```
---
**What am I do... | {
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```python
dataset = load_dataset('multi_nli')
```
I get this long error:
```python
---------------------------------------------------------------------------
OSError Traceback (most recent call last)
<ipython-input-13-3b11f6be4cb9> in <m... | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/236... | Hello,
Thanks for the amazing library that you put together. I'm Alessandro Suglia, the first author of CompGuessWhat?!, a recently released dataset for grounded language learning accepted to ACL 2020 ([https://compguesswhat.github.io](https://compguesswhat.github.io)).
This pull-request adds the CompGuessWhat?! ... | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/235... | ## Adding an *experimental datasets* folder
After using the 🤗nlp library for some time, I find that while it makes it super easy to create new memory-mapped datasets with lots of cool utilities, a lot of what I want to do doesn't work well with the current `MockDownloader` based testing paradigm, making it hard to ... | {
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Does anyone know how we can call our custom dataset using the nlp.load command? Let's say that I have a dataset based on the same format as that of squad-v1.1, how am I supposed to load it using huggingface nlp.
Thank you! | {
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```
dataset = nlp.load_dataset('c4', 'en', beam_runner='DirectRunner'
, data_dir='/mypath')
```
and i met failure as follows
```
Downloading and preparing dataset c4/en (download: Unknown size, generated: Unknown size, total: Unknown size) to /home/adam/.... | {
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As mentioned in #181, I had to use the new endpoints and revert the use of dataclasses (just in case we have changes in the API in the future).
We now distinguish commands for datasets and commands for metrics:
```bash
nlp-cli upload_data... | {
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} | As the file required for the viewing in the live nlp viewer is named as dataset_info.json | {
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```
FileNotFoundError: [Errno 2] No such file or directory: '/home/sasha/.cache/huggingface/datasets/xnli/plain_text/1.0.0/dataset_info.json'
Traceback:
File "/... | {
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"gists... | null | [] | 2020-06-03T09:33:20Z | 2020-06-03T15:25:41Z | 2020-06-03T15:25:41Z | CONTRIBUTOR | null | null | null | Hi, first thanks to @lhoestq 's revolutionary work, I successfully downloaded processed wikipedia according to the doc. 😍😍😍
But at the first try, it tell me to install `apache_beam` and `mwparserfromhell`, which I thought wouldn't be used according to #204 , it was kind of confusing me at that time.
Maybe we s... | {
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Here is a self-contained notebook to reproduce both scores : https://colab.research.google.com/drive/14EyAXValB6UzKY9x4rs_T3pyL7alpw_F?usp=sharing
---
`nlp` : (Only mid F-scores)
>rouge1 0.33508031962733364
rouge2 0.145743337761... | {
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I think it would be interesting to add the FLUE dataset for francophones or anyone wishing to work on French.
In other requests, I read that you are already working on some datasets, and I was wondering if FLUE was planned.
If it is not the case, I can provide each of the cleaned FLUE datasets (in the form... | {
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https://colab.research.google.com/github/huggingface/nlp/blob/master/notebooks/Overview.ipynb
breaks when running this cell:
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However they are not processed nor directly available from gcp yet. | {
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"default": fals... | open | false | null | [] | null | [] | 2020-05-29T09:22:26Z | 2022-10-22T00:45:50Z | null | CONTRIBUTOR | null | null | null | It seems like many of the best performing models on the GLUE benchmark make some use of multitask learning (simultaneous training on multiple tasks).
The [T5 paper](https://arxiv.org/pdf/1910.10683.pdf) highlights multiple ways of mixing the tasks together during finetuning:
- **Examples-proportional mixing** - sam... | {
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---
I compute scores with :
```python
import nlp
rouge = nlp.load_metric('rouge')
with open("pred.txt") as p, open("ref.txt") as g:
for lp, lg in zip(p, g):
rouge.add([lp], [lg])
score = rouge.compute()
```
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```
raise NonMatchingSplitsSizesError(str(bad_splits))
nlp.utils.info_utils.NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='train',
num_bytes=610252351, num_examples=532812, dataset_name='blog_authorship_corpus'),
'recorded... | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/214... | The `.map()` function is super useful, but can IMO a bit tedious when filtering certain examples.
I think, filtering out examples is also a very common operation people would like to perform on datasets.
This PR is a proposal to add a `.filter()` function in the same spirit than the `.map()` function.
Here is a ... | {
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For example:
```python
dataset = nlp.load_dataset('wikipedia', '20200501.aa')
```
Raises:
```
MissingBeamOptions: Trying to generate a dataset using Apache Beam, yet no Beam Runner or PipelineOptions() has been provided in `load_dataset` or in the builder arguments. For big datasets it has to ru... | {
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Previously the `.add` method of metrics expected a batch of examples.
Now `.add` expects one prediction/reference and `.add_batch` expects a batch.
I think it is more coherent with the way the ArrowWriter works. | {
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```
import nlp
ds = nlp.load_dataset("trivia_qa", "rc", split="validation[:1%]") # this might take 2.3 min to download but it's cached afterwards...
ds.map(lambda x: x, load_from_cache_file=False)
```
triggers a `ArrowInvalid: Could not convert TagMe with type str: converting to n... | {
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https://api.github.com/repos/huggingface/datasets/issues/210 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/210/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/210/comments | https://api.github.com/repos/huggingface/datasets/issues/210/events | https://github.com/huggingface/datasets/pull/210 | 626,504,243 | MDExOlB1bGxSZXF1ZXN0NDI0NDgyNDgz | 210 | fix xnli metric kwargs description | {
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https://api.github.com/repos/huggingface/datasets/issues/209 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/209/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/209/comments | https://api.github.com/repos/huggingface/datasets/issues/209/events | https://github.com/huggingface/datasets/pull/209 | 626,405,849 | MDExOlB1bGxSZXF1ZXN0NDI0NDAwOTc4 | 209 | Add a Google Drive exception for small files | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/209... | I tried to use the ``nlp`` library to load personnal datasets. I mainly copy-paste the code for ``multi-news`` dataset because my files are stored on Google Drive.
One of my dataset is small (< 25Mo) so it can be verified by Drive without asking the authorization to the user. This makes the download starts directly... | {
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Also, @lhoestq fixed small import bug introduced by beam command I think. | {
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https://api.github.com/repos/huggingface/datasets/issues/207 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/207/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/207/comments | https://api.github.com/repos/huggingface/datasets/issues/207/events | https://github.com/huggingface/datasets/issues/207 | 625,932,200 | MDU6SXNzdWU2MjU5MzIyMDA= | 207 | Remove test set from NLP viewer | {
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https://api.github.com/repos/huggingface/datasets/issues/206 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/206/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/206/comments | https://api.github.com/repos/huggingface/datasets/issues/206/events | https://github.com/huggingface/datasets/issues/206 | 625,842,989 | MDU6SXNzdWU2MjU4NDI5ODk= | 206 | [Question] Combine 2 datasets which have the same columns | {
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I am using ``nlp`` to load personal datasets. I created summarization datasets in multi-languages based on wikinews. I have one dataset for english and one for german (french is getting to be ready as well). I want to keep these datasets independent because they need different pre-processing (add different task-... | {
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With these changes I should be able to come up with a `tf.data.Dataset` that uses lazy loading, as asked in #193. | {
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https://api.github.com/repos/huggingface/datasets/issues/204 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/204/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/204/comments | https://api.github.com/repos/huggingface/datasets/issues/204/events | https://github.com/huggingface/datasets/pull/204 | 625,655,849 | MDExOlB1bGxSZXF1ZXN0NDIzODE5MTQw | 204 | Add Dataflow support + Wikipedia + Wiki40b | {
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## Support datasets processing with Apache Beam
Some datasets are too big to be processed on a single machine, for example: wikipedia, wiki40b, etc. Apache Beam allows to process datasets on many execution engines like Dataflow, Spark, Flink, etc.
To process such da... | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/203... | Some datasets like glue (see #130) and scientific_papers (see #197) have many configs.
For example for glue there are cola, sst2, mrpc etc.
Currently if a user does `load_dataset('glue')`, then Cola is loaded by default and it can be confusing. Instead, we should raise an error to let the user know that he has to p... | {
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https://api.github.com/repos/huggingface/datasets/issues/202 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/202/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/202/comments | https://api.github.com/repos/huggingface/datasets/issues/202/events | https://github.com/huggingface/datasets/issues/202 | 625,493,983 | MDU6SXNzdWU2MjU0OTM5ODM= | 202 | Mistaken `_KWARGS_DESCRIPTION` for XNLI metric | {
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The [`_KWARGS_DESCRIPTION`](https://github.com/huggingface/nlp/blob/7d0fa58641f3f462fb2861dcdd6ce7f0da3f6a56/metrics/xnli/xnli.py#L45) for the XNLI metric uses `Args` and `Returns` text from [BLEU](https://github.com/huggingface/nlp/blob/7d0fa58641f3f462fb2861dcdd6ce7f0da3f6a56/metrics/bleu/bleu.py#L58) metric:
... | {
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https://api.github.com/repos/huggingface/datasets/issues/201 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/201/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/201/comments | https://api.github.com/repos/huggingface/datasets/issues/201/events | https://github.com/huggingface/datasets/pull/201 | 625,235,430 | MDExOlB1bGxSZXF1ZXN0NDIzNDkzNTMw | 201 | Fix typo in README | {
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https://api.github.com/repos/huggingface/datasets/issues/200 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/200/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/200/comments | https://api.github.com/repos/huggingface/datasets/issues/200/events | https://github.com/huggingface/datasets/pull/200 | 625,226,638 | MDExOlB1bGxSZXF1ZXN0NDIzNDg2NTM0 | 200 | [ArrowWriter] Set schema at first write example | {
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"url": "https://api.github.com/repos/huggingface/datasets/pulls/200... | Right now if the schema was not specified when instantiating `ArrowWriter`, then it could be set with the first `write_table` for example (it calls `self._build_writer()` to do so).
I noticed that it was not done if the first example is added via `.write`, so I added it for coherence. | {
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https://api.github.com/repos/huggingface/datasets/issues/199 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/199/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/199/comments | https://api.github.com/repos/huggingface/datasets/issues/199/events | https://github.com/huggingface/datasets/pull/199 | 625,217,440 | MDExOlB1bGxSZXF1ZXN0NDIzNDc4ODIx | 199 | Fix GermEval 2014 dataset infos | {
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this PR just removes the `dataset_info.json` file and adds a newly generated `dataset_infos.json` file. | {
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https://api.github.com/repos/huggingface/datasets/issues/198 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/198/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/198/comments | https://api.github.com/repos/huggingface/datasets/issues/198/events | https://github.com/huggingface/datasets/issues/198 | 625,200,627 | MDU6SXNzdWU2MjUyMDA2Mjc= | 198 | Index outside of table length | {
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> ValueError: Index (2000) outside of table length (2000).
> Traceback:
> File "/home/sasha/.local/lib/python3.7/site-packages/streamlit/ScriptRunner.py", line 322, in _ru... | {
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https://api.github.com/repos/huggingface/datasets/issues/197 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/197/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/197/comments | https://api.github.com/repos/huggingface/datasets/issues/197/events | https://github.com/huggingface/datasets/issues/197 | 624,966,904 | MDU6SXNzdWU2MjQ5NjY5MDQ= | 197 | Scientific Papers only downloading Pubmed | {
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I have been playing around with this module, and I am a bit confused about the `scientific_papers` dataset. I thought that it would download two separate datasets, arxiv and pubmed. But when I run the following:
```
dataset = nlp.load_dataset('scientific_papers', data_dir='.', cache_dir='.')
Downloading: 10... | {
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https://api.github.com/repos/huggingface/datasets/issues/196 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/196/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/196/comments | https://api.github.com/repos/huggingface/datasets/issues/196/events | https://github.com/huggingface/datasets/pull/196 | 624,901,266 | MDExOlB1bGxSZXF1ZXN0NDIzMjIwMjIw | 196 | Check invalid config name | {
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Bad characters are those that are not allowed for directory names on windows. | {
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https://api.github.com/repos/huggingface/datasets/issues/195 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/195/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/195/comments | https://api.github.com/repos/huggingface/datasets/issues/195/events | https://github.com/huggingface/datasets/pull/195 | 624,858,686 | MDExOlB1bGxSZXF1ZXN0NDIzMTg1NTAy | 195 | [Dummy data command] add new case to command | {
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