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https://api.github.com/repos/huggingface/datasets/issues/338 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/338/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/338/comments | https://api.github.com/repos/huggingface/datasets/issues/338/events | https://github.com/huggingface/datasets/pull/338 | 650,057,253 | MDExOlB1bGxSZXF1ZXN0NDQzNjIxMTEx | 338 | Run `make style` | {
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```python
# use these existing methods
ds = load_dataset("wikitext", "wik... | {
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Namely, it would be really nice to add:
- WebQuestions (Berant et al., 2013) [done]
- CuratedTrec (Baudis et al. 2015) [not open-source]
- MS-MARCO (NGuyen et al. 2016) [done]
- SearchQA (Dunn et al.... | {
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Note on the implementation:
- There are two configs: with and without the embeddings (73G... | {
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] | closed | false | null | [] | null | 5 | 2020-06-30T22:21:33Z | 2020-07-09T13:03:40Z | 2020-07-09T13:03:40Z | CONTRIBUTOR | null | ```
>>> import nlp
>>> nlp.load_dataset('cnn_dailymail', '3.0.0')
Downloading and preparing dataset cnn_dailymail/3.0.0 (download: 558.32 MiB, generated: 1.26 GiB, total: 1.81 GiB) to /u/jm8wx/.cache/huggingface/datasets/cnn_dailymail/3.0.0/3.0.0...
Traceback (most recent call last):
File "<stdin>", line 1, in... | {
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- There are 2 separate versions of the training set - *annotated* and *distant*. Instead of `nlp.Split.Train` I've used the splits `"train_annotated"` and `"train_distant"` to ... | {
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`load_dataset("wikitext", "wikitext-2-raw-v1")`
But when I attempt to cache it on an external volume, it hangs indefinitely:
`load_dataset("wikitext", "wikitext-2-raw-v1", cache_dir="/fsx") # /fsx is an external volume mount`
The filesystem when hanging looks like thi... | {
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We're currently training a custom TensorFlow model but the nlp paradigm should be a bridge for us to be able to use the wealth of pre-trained models in Transformers.
Our preprocessing flow parses raw text and... | {
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Caused the computing power we splitted it into multiple tiles, but they are all in the same format.
Right now the most important facts about are this:
- Contexts: 1.047.671
- questions: 1.677... | {
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https://api.github.com/repos/huggingface/datasets/issues/325 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/325/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/325/comments | https://api.github.com/repos/huggingface/datasets/issues/325/events | https://github.com/huggingface/datasets/pull/325 | 647,601,592 | MDExOlB1bGxSZXF1ZXN0NDQxNTk3NTgw | 325 | Add SQuADShifts dataset | {
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https://api.github.com/repos/huggingface/datasets/issues/324 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/324/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/324/comments | https://api.github.com/repos/huggingface/datasets/issues/324/events | https://github.com/huggingface/datasets/issues/324 | 647,525,725 | MDU6SXNzdWU2NDc1MjU3MjU= | 324 | Error when calculating glue score | {
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```
import nlp
glue_metric = nlp.load_metric('glue',name="cola")
glue_score = glue_metric.compute(predictions, references)
```
```
---------------------------------------------------------------------------
--------------... | {
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https://api.github.com/repos/huggingface/datasets/issues/323 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/323/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/323/comments | https://api.github.com/repos/huggingface/datasets/issues/323/events | https://github.com/huggingface/datasets/pull/323 | 647,521,308 | MDExOlB1bGxSZXF1ZXN0NDQxNTMxOTY3 | 323 | Add package path to sys when downloading package as github archive | {
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@thomwolf not sure how you feel about adding to the `PYTHONPATH` from the script. This is the only way I could make it work with my understanding of `importli... | {
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https://api.github.com/repos/huggingface/datasets/issues/322 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/322/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/322/comments | https://api.github.com/repos/huggingface/datasets/issues/322/events | https://github.com/huggingface/datasets/pull/322 | 647,483,850 | MDExOlB1bGxSZXF1ZXN0NDQxNTAyMjc2 | 322 | output nested dict in get_nearest_examples | {
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```python
my_examples = dataset[0:10]
print(type(my_examples))
# >>> dict
print(my_examples["my_column"][0]
# >>> this is the first element of the colum... | {
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I am trying to download some wikipedia data but I got this error for spanish "es" (but there are maybe some others languages which have the same error I haven't tried all of them ).
`ERROR:root:mwparserfromhell ParseError: This is a bug and should be reported. Info: C tokenizer exited with non-empty token sta... | {
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https://api.github.com/repos/huggingface/datasets/issues/320 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/320/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/320/comments | https://api.github.com/repos/huggingface/datasets/issues/320/events | https://github.com/huggingface/datasets/issues/320 | 647,188,167 | MDU6SXNzdWU2NDcxODgxNjc= | 320 | Blog Authorship Corpus, Non Matching Splits Sizes Error, nlp viewer | {
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```
NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='train', num_bytes=610252351, num_examples=532812, dataset_name='blog_authorship_corpus'), 'recorded': SplitInfo(name='train', num_bytes=614706451, num_examples=535568, dat... | {
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https://api.github.com/repos/huggingface/datasets/issues/319 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/319/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/319/comments | https://api.github.com/repos/huggingface/datasets/issues/319/events | https://github.com/huggingface/datasets/issues/319 | 646,792,487 | MDU6SXNzdWU2NDY3OTI0ODc= | 319 | Nested sequences with dicts | {
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The original data is in this form... | {
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https://api.github.com/repos/huggingface/datasets/issues/318 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/318/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/318/comments | https://api.github.com/repos/huggingface/datasets/issues/318/events | https://github.com/huggingface/datasets/pull/318 | 646,682,840 | MDExOlB1bGxSZXF1ZXN0NDQwOTExOTYy | 318 | Multitask | {
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There's a function `build_multitask()` which takes either individual `nlp.Dataset`s or `dicts` of splits and constructs `MultiDataset`(s). I've added a notebook with example usage.
I've implemented many of the `nlp.Datas... | {
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https://api.github.com/repos/huggingface/datasets/issues/317 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/317/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/317/comments | https://api.github.com/repos/huggingface/datasets/issues/317/events | https://github.com/huggingface/datasets/issues/317 | 646,555,384 | MDU6SXNzdWU2NDY1NTUzODQ= | 317 | Adding a dataset with multiple subtasks | {
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For example, in [QE 201... | {
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] | open | false | null | [] | null | 11 | 2020-06-25T22:30:20Z | 2020-10-27T15:38:17Z | null | CONTRIBUTOR | null | I'm training on large datasets such as Wikipedia and BookCorpus. Following the instructions in [the tutorial notebook](https://colab.research.google.com/github/huggingface/nlp/blob/master/notebooks/Overview.ipynb), I see the following recommended for TensorFlow:
```python
train_tf_dataset = train_tf_dataset.filter(... | {
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Code is heavily bo... | {
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```python
rank = 3 # for example
size = 10
dataset = nlp.load_dataset('wikitext', 'wikitext-2-raw-v1', split=f"train[{rank*10}%:{(rank+1)*10}%]")
```
However, this breaks down if you have a number of ranks that doesn't divide cleanly... | {
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A common processing step seems to be replacing the `XXX` placeholder with the `subject`. I've left this out as it's something you could easily do with `map`. | {
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Interesting things to note:
- Have copied the function (`_convert_to_human_readable`) which converts the SQL query to a human-readable (string) format as this is what most people will want when actually using this dataset for NLP applications.
- ... | {
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Only contains data for summaries (not whole story) | {
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```python
dataset = nlp.load_dataset('glue', 'mrpc')
```
```python
Downloading and preparing dataset glue/mrpc (download: Unknown size, generated: Unknown size, total: Unknown size) to C:\Users\Python\.cache... | {
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Add functioning PG19 dataset with dummy data
`cos_e.py` was just auto-linted by `make style` | {
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Currently however, the code seems to... | {
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Attached [Colab](https://colab.research.google.com/drive/13H0ZgyQ2se0mqJ2yyew0bNEgJuHaJ8H3?usp=sharing) Notebook for problem ... | {
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Therefore it can happen that we try to move files across filesystems.
We were using `os.rename` that doesn't allow that, so I changed some of them to `shutil.move`.
This should fix #301 | {
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I was wondering about adding datasets here, specifically because it's shaping up to be large and easily usable.
The metrics for sign language to text translation are the same.
So, what do you think about (me, or others) adding datasets here?
An exa... | {
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```
nlp.load_dataset('wikipedia', '20200501.de', split = 'train', cache_dir=my_path)
```
```
OSError ... | {
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Moreover I added support for both strings and lists of strings for `references` in `bertscore`, as it is the case in the original code.
Both... | {
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I was working on adding Indexed Datasets but in the meantime I had to also add more support for Numpy arrays in the lib.
## Better support for Numpy format
New features:
- New fast method to convert Numpy arrays from Arrow structure (up to x100 speed up... | {
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```
import nlp
from collections import Counter
data = nlp.load_dataset('snli')['train']
print(Counter(data['label']))
Counter({0: 183416, 2: 183187, 1: 182764, -1: 785})
```
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I am the author of `bert_score`. Recently, we received [ an issue ](https://github.com/Tiiiger/bert_score/issues/62) reporting a problem in using `bert_score` from the `nlp` package (also see #238 in this repo). After looking into this, I realized that the problem arises from the format `nlp.Metric` takes inpu... | {
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```python
arxiv = nlp.load_dataset("scientific_papers", "arxiv")
```
I get the following stack trace:
```bash
JSONDecodeError Traceback (most recen... | {
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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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- 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)])
/Users/... | {
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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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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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**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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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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... | [] | closed | false | null | [] | null | 6 | 2020-06-13T10:12:10Z | 2020-06-18T07:41:21Z | 2020-06-18T07:41:20Z | CONTRIBUTOR | null | 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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"gists... | null | 0 | 2020-06-13T06:26:54Z | 2020-06-18T07:41:44Z | 2020-06-18T07:41:44Z | NONE | 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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- `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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https://api.github.com/repos/huggingface/datasets/issues/265 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/265/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/265/comments | https://api.github.com/repos/huggingface/datasets/issues/265/events | https://github.com/huggingface/datasets/pull/265 | 637,139,220 | MDExOlB1bGxSZXF1ZXN0NDMzMTgxNDMz | 265 | Add pyarrow warning colab | {
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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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- 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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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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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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https://api.github.com/repos/huggingface/datasets/issues/257 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/257/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/257/comments | https://api.github.com/repos/huggingface/datasets/issues/257/events | https://github.com/huggingface/datasets/issues/257 | 635,620,979 | MDU6SXNzdWU2MzU2MjA5Nzk= | 257 | Tokenizer pickling issue fix not landed in `nlp` yet? | {
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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/255 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/255/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/255/comments | https://api.github.com/repos/huggingface/datasets/issues/255/events | https://github.com/huggingface/datasets/pull/255 | 635,300,822 | MDExOlB1bGxSZXF1ZXN0NDMxNjg3MDM0 | 255 | Add dataset/piaf | {
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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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https://api.github.com/repos/huggingface/datasets/issues/253 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/253/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/253/comments | https://api.github.com/repos/huggingface/datasets/issues/253/events | https://github.com/huggingface/datasets/pull/253 | 634,791,939 | MDExOlB1bGxSZXF1ZXN0NDMxMjgwOTYz | 253 | add flue dataset | {
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https://api.github.com/repos/huggingface/datasets/issues/252 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/252/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/252/comments | https://api.github.com/repos/huggingface/datasets/issues/252/events | https://github.com/huggingface/datasets/issues/252 | 634,563,239 | MDU6SXNzdWU2MzQ1NjMyMzk= | 252 | NonMatchingSplitsSizesError error when reading the IMDB dataset | {
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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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https://api.github.com/repos/huggingface/datasets/issues/251 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/251/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/251/comments | https://api.github.com/repos/huggingface/datasets/issues/251/events | https://github.com/huggingface/datasets/pull/251 | 634,544,977 | MDExOlB1bGxSZXF1ZXN0NDMxMDgwMDkw | 251 | Better access to all dataset information | {
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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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https://api.github.com/repos/huggingface/datasets/issues/250 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/250/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/250/comments | https://api.github.com/repos/huggingface/datasets/issues/250/events | https://github.com/huggingface/datasets/pull/250 | 634,416,751 | MDExOlB1bGxSZXF1ZXN0NDMwOTcyMzg4 | 250 | Remove checksum download in c4 | {
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"gists_url": "https:... | [] | closed | false | null | [] | null | 1 | 2020-06-08T09:13:00Z | 2020-08-25T07:04:56Z | 2020-06-08T09:16:59Z | MEMBER | null | 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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https://api.github.com/repos/huggingface/datasets/issues/249 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/249/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/249/comments | https://api.github.com/repos/huggingface/datasets/issues/249/events | https://github.com/huggingface/datasets/issues/249 | 633,393,443 | MDU6SXNzdWU2MzMzOTM0NDM= | 249 | [Dataset created] some critical small issues when I was creating a dataset | {
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"gists... | null | 2 | 2020-06-07T12:58:54Z | 2020-06-12T08:28:51Z | 2020-06-12T08:28:51Z | CONTRIBUTOR | 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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"gist... | [] | closed | false | null | [] | null | 11 | 2020-06-07T12:54:56Z | 2020-06-12T08:45:03Z | 2020-06-12T08:45:02Z | CONTRIBUTOR | null | 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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https://api.github.com/repos/huggingface/datasets/issues/247 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/247/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/247/comments | https://api.github.com/repos/huggingface/datasets/issues/247/events | https://github.com/huggingface/datasets/pull/247 | 632,380,078 | MDExOlB1bGxSZXF1ZXN0NDI5MTMwMzQ2 | 247 | Make all dataset downloads deterministic by applying `sorted` to glob and os.listdir | {
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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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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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https://api.github.com/repos/huggingface/datasets/issues/243 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/243/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/243/comments | https://api.github.com/repos/huggingface/datasets/issues/243/events | https://github.com/huggingface/datasets/pull/243 | 631,735,848 | MDExOlB1bGxSZXF1ZXN0NDI4NTY2MTEy | 243 | Specify utf-8 encoding for GLUE | {
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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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https://api.github.com/repos/huggingface/datasets/issues/242 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/242/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/242/comments | https://api.github.com/repos/huggingface/datasets/issues/242/events | https://github.com/huggingface/datasets/issues/242 | 631,733,683 | MDU6SXNzdWU2MzE3MzM2ODM= | 242 | UnicodeDecodeError when downloading GLUE-MNLI | {
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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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https://api.github.com/repos/huggingface/datasets/issues/241 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/241/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/241/comments | https://api.github.com/repos/huggingface/datasets/issues/241/events | https://github.com/huggingface/datasets/pull/241 | 631,703,079 | MDExOlB1bGxSZXF1ZXN0NDI4NTQwMDM0 | 241 | Fix empty cache dir | {
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https://api.github.com/repos/huggingface/datasets/issues/240 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/240/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/240/comments | https://api.github.com/repos/huggingface/datasets/issues/240/events | https://github.com/huggingface/datasets/issues/240 | 631,434,677 | MDU6SXNzdWU2MzE0MzQ2Nzc= | 240 | Deterministic dataset loading | {
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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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https://api.github.com/repos/huggingface/datasets/issues/239 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/239/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/239/comments | https://api.github.com/repos/huggingface/datasets/issues/239/events | https://github.com/huggingface/datasets/issues/239 | 631,340,440 | MDU6SXNzdWU2MzEzNDA0NDA= | 239 | [Creating new dataset] Not found dataset_info.json | {
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"gists... | null | 5 | 2020-06-05T06:15:04Z | 2020-06-07T13:01:04Z | 2020-06-07T13:01:04Z | CONTRIBUTOR | 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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