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https://api.github.com/repos/huggingface/datasets/issues/276 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/276/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/276/comments | https://api.github.com/repos/huggingface/datasets/issues/276/events | https://github.com/huggingface/datasets/pull/276 | 639,490,858 | MDExOlB1bGxSZXF1ZXN0NDM1MDY5Nzg5 | 276 | Fix metric compute (original_instructions missing) | {
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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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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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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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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/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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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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"g... | [] | closed | false | null | [] | null | 10 | 2020-06-08T17:11:09Z | 2020-07-16T07:50:59Z | 2020-07-16T07:50:59Z | CONTRIBUTOR | null | This PR add the Flue dataset as requested in this issue #223 . @lbourdois made a detailed description in that issue.
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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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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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"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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```
@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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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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```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 | 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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"color": "25b21e",
"default": false,
"description": "A bug in a metric script",
"id": 2067393914,
"name": "metric bug",
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] | closed | false | null | [] | null | 1 | 2020-06-05T02:14:47Z | 2020-06-29T17:10:19Z | 2020-06-29T17:10:19Z | NONE | null | When running BERT-Score, I'm meeting this warning :
> 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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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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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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@yjernite | {
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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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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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"gi... | null | 3 | 2020-06-01T00:50:36Z | 2020-06-03T15:27:18Z | 2020-06-03T15:27:18Z | NONE | null | It seems that the ROUGE score of `nlp` is lower than the one of `files2rouge`.
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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"gi... | null | 5 | 2020-05-30T18:30:40Z | 2023-01-19T15:46:58Z | 2021-01-04T09:53:32Z | NONE | null | Hi, I am interested in porting google research's new BLEURT learned metric to PyTorch (because I wish to do something experimental with language generation and backpropping through BLEURT). I noticed that you guys don't have it yet so I am partly just asking if you plan to add it (@thomwolf said you want to do so on Tw... | {
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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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https://api.github.com/repos/huggingface/datasets/issues/219 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/219/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/219/comments | https://api.github.com/repos/huggingface/datasets/issues/219/events | https://github.com/huggingface/datasets/pull/219 | 627,235,893 | MDExOlB1bGxSZXF1ZXN0NDI1MDc2NjQx | 219 | force mwparserfromhell as third party | {
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https://api.github.com/repos/huggingface/datasets/issues/218 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/218/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/218/comments | https://api.github.com/repos/huggingface/datasets/issues/218/events | https://github.com/huggingface/datasets/pull/218 | 627,173,407 | MDExOlB1bGxSZXF1ZXN0NDI1MDI2NzEz | 218 | Add Natual Questions and C4 scripts | {
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However they are not processed nor directly available from gcp yet. | {
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https://api.github.com/repos/huggingface/datasets/issues/217 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/217/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/217/comments | https://api.github.com/repos/huggingface/datasets/issues/217/events | https://github.com/huggingface/datasets/issues/217 | 627,128,403 | MDU6SXNzdWU2MjcxMjg0MDM= | 217 | Multi-task dataset mixing | {
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"default": fals... | open | false | null | [] | null | 26 | 2020-05-29T09:22:26Z | 2022-10-22T00:45:50Z | null | CONTRIBUTOR | 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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https://api.github.com/repos/huggingface/datasets/issues/216 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/216/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/216/comments | https://api.github.com/repos/huggingface/datasets/issues/216/events | https://github.com/huggingface/datasets/issues/216 | 626,896,890 | MDU6SXNzdWU2MjY4OTY4OTA= | 216 | ❓ How to get ROUGE-2 with the ROUGE metric ? | {
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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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https://api.github.com/repos/huggingface/datasets/issues/215 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/215/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/215/comments | https://api.github.com/repos/huggingface/datasets/issues/215/events | https://github.com/huggingface/datasets/issues/215 | 626,867,879 | MDU6SXNzdWU2MjY4Njc4Nzk= | 215 | NonMatchingSplitsSizesError when loading blog_authorship_corpus | {
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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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https://api.github.com/repos/huggingface/datasets/issues/214 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/214/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/214/comments | https://api.github.com/repos/huggingface/datasets/issues/214/events | https://github.com/huggingface/datasets/pull/214 | 626,641,549 | MDExOlB1bGxSZXF1ZXN0NDI0NTk1NjIx | 214 | [arrow_dataset.py] add new filter function | {
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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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https://api.github.com/repos/huggingface/datasets/issues/213 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/213/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/213/comments | https://api.github.com/repos/huggingface/datasets/issues/213/events | https://github.com/huggingface/datasets/pull/213 | 626,587,995 | MDExOlB1bGxSZXF1ZXN0NDI0NTUxODE3 | 213 | better message if missing beam options | {
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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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https://api.github.com/repos/huggingface/datasets/issues/212 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/212/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/212/comments | https://api.github.com/repos/huggingface/datasets/issues/212/events | https://github.com/huggingface/datasets/pull/212 | 626,580,198 | MDExOlB1bGxSZXF1ZXN0NDI0NTQ1NjAy | 212 | have 'add' and 'add_batch' for metrics | {
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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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"gis... | null | 7 | 2020-05-28T14:38:14Z | 2020-07-23T10:15:16Z | 2020-07-23T10:15:16Z | MEMBER | null | Running the following code
```
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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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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https://api.github.com/repos/huggingface/datasets/issues/208 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/208/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/208/comments | https://api.github.com/repos/huggingface/datasets/issues/208/events | https://github.com/huggingface/datasets/pull/208 | 626,398,519 | MDExOlB1bGxSZXF1ZXN0NDI0Mzk0ODIx | 208 | [Dummy data] insert config name instead of config | {
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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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https://api.github.com/repos/huggingface/datasets/issues/205 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/205/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/205/comments | https://api.github.com/repos/huggingface/datasets/issues/205/events | https://github.com/huggingface/datasets/pull/205 | 625,839,335 | MDExOlB1bGxSZXF1ZXN0NDIzOTY2ODE1 | 205 | Better arrow dataset iter | {
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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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https://api.github.com/repos/huggingface/datasets/issues/203 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/203/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/203/comments | https://api.github.com/repos/huggingface/datasets/issues/203/events | https://github.com/huggingface/datasets/pull/203 | 625,515,488 | MDExOlB1bGxSZXF1ZXN0NDIzNzEyMTQ3 | 203 | Raise an error if no config name for datasets like glue | {
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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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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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> 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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Bad characters are those that are not allowed for directory names on windows. | {
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```python
columns = ['input_ids', 'token_type_ids', 'attention_mask', 'start_positions', 'end_positions']
train_tf_dataset.set_format(type='tensorflow', columns=columns)
features = {x: train_tf_dataset[x] for x in columns[:3]}
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Is the worth of send it to you and add i... | {
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Fixes #164 | {
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* `WARNING:nlp.builder:Trying to generate a dataset using Apache Beam, yet no Beam Runner or PipelineOptions() has been provided. Please pass a nlp.DownloadConfig(beam_runner=...) object to the builder.download_and_prepare(download_config=...) method. Default values will be ... | {
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https://api.github.com/repos/huggingface/datasets/issues/186 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/186/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/186/comments | https://api.github.com/repos/huggingface/datasets/issues/186/events | https://github.com/huggingface/datasets/issues/186 | 623,595,180 | MDU6SXNzdWU2MjM1OTUxODA= | 186 | Weird-ish: Not creating unique caches for different phases | {
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```python
import nlp
dataset = nlp.load_dataset('boolq')
def func1(x):
return x
def func2(x):
return None
train_output = dataset["train"].map(func1)
valid_output = dataset["validation"].map(func1)
print()
print(len(train_output), len(valid_output))
# Output: 9427 9427
```
Th... | {
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This PR adds a new command `python nlp-cli dummy_data <path_to_dataset_folder>` that gives in-detail instructions on how to add the dummy data files.
It would be great if you can try it out by moving the current dummy_data folder of any dataset in `./datasets` with `mv datasets/<dataset_s... | {
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"gist... | [] | closed | false | null | [] | null | 0 | 2020-05-22T10:43:42Z | 2020-05-28T08:31:18Z | 2020-05-28T08:31:18Z | CONTRIBUTOR | null | **`default __iter__ needs IndexError`**.
When I want to create a wrapper of arrow dataset to adapt to fastai,
I don't know how to initialize it, so I didn't use inheritance but use object composition.
I wrote sth like this.
```
clas HF_dataset():
def __init__(self, arrow_dataset):
self.dset = arrow_datas... | {
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https://api.github.com/repos/huggingface/datasets/issues/183 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/183/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/183/comments | https://api.github.com/repos/huggingface/datasets/issues/183/events | https://github.com/huggingface/datasets/issues/183 | 623,054,270 | MDU6SXNzdWU2MjMwNTQyNzA= | 183 | [Bug] labels of glue/ax are all -1 | {
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"gists... | null | 2 | 2020-05-22T08:43:36Z | 2020-05-22T22:14:05Z | 2020-05-22T22:14:05Z | CONTRIBUTOR | null | ```
ax = nlp.load_dataset('glue', 'ax')
for i in range(30): print(ax['test'][i]['label'], end=', ')
```
```
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``` | {
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https://api.github.com/repos/huggingface/datasets/issues/182 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/182/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/182/comments | https://api.github.com/repos/huggingface/datasets/issues/182/events | https://github.com/huggingface/datasets/pull/182 | 622,646,770 | MDExOlB1bGxSZXF1ZXN0NDIxNDcxMjg4 | 182 | Update newsroom.py | {
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"following_url": "https://api.github.com/users/patrickvonplaten/followin... | null | 0 | 2020-05-21T17:07:43Z | 2020-05-22T16:38:23Z | 2020-05-22T16:38:23Z | CONTRIBUTOR | null | Updated the URL for Newsroom download so it's more robust to future changes. | {
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https://api.github.com/repos/huggingface/datasets/issues/181 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/181/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/181/comments | https://api.github.com/repos/huggingface/datasets/issues/181/events | https://github.com/huggingface/datasets/issues/181 | 622,634,420 | MDU6SXNzdWU2MjI2MzQ0MjA= | 181 | Cannot upload my own dataset | {
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It is supposed to work like this
- Register to get username, password at huggingface.co
- `nlp-cli login` and type username, passworld
- I have a single file to upload at `./ttc/ttc_freq_extra.csv`
- `nlp-cli upload ttc/ttc_freq_extra.csv`
... | {
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https://api.github.com/repos/huggingface/datasets/issues/180 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/180/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/180/comments | https://api.github.com/repos/huggingface/datasets/issues/180/events | https://github.com/huggingface/datasets/pull/180 | 622,556,861 | MDExOlB1bGxSZXF1ZXN0NDIxMzk5Nzg2 | 180 | Add hall of fame | {
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https://api.github.com/repos/huggingface/datasets/issues/179 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/179/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/179/comments | https://api.github.com/repos/huggingface/datasets/issues/179/events | https://github.com/huggingface/datasets/issues/179 | 622,525,410 | MDU6SXNzdWU2MjI1MjU0MTA= | 179 | [Feature request] separate split name and split instructions | {
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"gists... | null | 2 | 2020-05-21T14:10:51Z | 2020-05-22T13:31:08Z | 2020-05-22T13:31:07Z | MEMBER | null | Currently, the name of an nlp.NamedSplit is parsed in arrow_reader.py and used as the instruction.
This makes it impossible to have several training sets, which can occur when:
- A dataset corresponds to a collection of sub-datasets
- A dataset was built in stages, adding new examples at each stage
Would it be ... | {
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I guess the manual download instructions for `xsum` can also be improved. | {
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https://api.github.com/repos/huggingface/datasets/issues/177 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/177/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/177/comments | https://api.github.com/repos/huggingface/datasets/issues/177/events | https://github.com/huggingface/datasets/pull/177 | 621,975,368 | MDExOlB1bGxSZXF1ZXN0NDIwOTI4MzE0 | 177 | Xsum manual download instruction | {
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