Datasets:

Multilinguality:
multilingual
Language Creators:
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Annotations Creators:
no-annotation
Source Datasets:
original
ArXiv:
Tags:
License:
system HF staff commited on
Commit
02fc876
1 Parent(s): 7ceb319

Update files from the datasets library (from 1.7.0)

Browse files

Release notes: https://github.com/huggingface/datasets/releases/tag/1.7.0

Files changed (2) hide show
  1. README.md +6 -5
  2. oscar.py +1 -1
README.md CHANGED
@@ -116,7 +116,7 @@ languages:
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  - new
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  - nl
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  - nn
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- - "no"
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  - oc
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  - or
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  - os
@@ -845,6 +845,7 @@ task_categories:
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  - sequence-modeling
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  task_ids:
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  - language-modeling
 
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  ---
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  # Dataset Card for "oscar"
@@ -852,12 +853,12 @@ task_ids:
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  ## Table of Contents
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  - [Dataset Description](#dataset-description)
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  - [Dataset Summary](#dataset-summary)
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- - [Supported Tasks](#supported-tasks)
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  - [Languages](#languages)
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  - [Dataset Structure](#dataset-structure)
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  - [Data Instances](#data-instances)
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  - [Data Fields](#data-fields)
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- - [Data Splits Sample Size](#data-splits-sample-size)
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  - [Dataset Creation](#dataset-creation)
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  - [Curation Rationale](#curation-rationale)
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  - [Source Data](#source-data)
@@ -884,7 +885,7 @@ task_ids:
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  OSCAR or **O**pen **S**uper-large **C**rawled [**A**LMAnaCH](https://team.inria.fr/almanach/) co**R**pus is a huge multilingual corpus obtained by language classification and filtering of the [Common Crawl](https://commoncrawl.org/) corpus using the [goclassy](https://github.com/pjox/goclassy) architecture. Data is distributed by language in both original and deduplicated form.
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- ### Supported Tasks
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  OSCAR is mainly inteded to pretrain language models and word represantations.
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@@ -6137,7 +6138,7 @@ The data fields are the same among all configs.
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  - `id`: a `int64` feature.
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  - `text`: a `string` feature.
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- ### Data Splits Sample Size
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  <details>
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  - new
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  - nl
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  - nn
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+ - 'no'
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  - oc
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  - or
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  - os
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  - sequence-modeling
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  task_ids:
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  - language-modeling
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+ paperswithcode_id: oscar
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  ---
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  # Dataset Card for "oscar"
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  ## Table of Contents
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  - [Dataset Description](#dataset-description)
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  - [Dataset Summary](#dataset-summary)
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+ - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
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  - [Languages](#languages)
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  - [Dataset Structure](#dataset-structure)
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  - [Data Instances](#data-instances)
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  - [Data Fields](#data-fields)
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+ - [Data Splits](#data-splits)
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  - [Dataset Creation](#dataset-creation)
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  - [Curation Rationale](#curation-rationale)
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  - [Source Data](#source-data)
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  OSCAR or **O**pen **S**uper-large **C**rawled [**A**LMAnaCH](https://team.inria.fr/almanach/) co**R**pus is a huge multilingual corpus obtained by language classification and filtering of the [Common Crawl](https://commoncrawl.org/) corpus using the [goclassy](https://github.com/pjox/goclassy) architecture. Data is distributed by language in both original and deduplicated form.
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+ ### Supported Tasks and Leaderboards
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  OSCAR is mainly inteded to pretrain language models and word represantations.
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  - `id`: a `int64` feature.
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  - `text`: a `string` feature.
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+ ### Data Splits
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  <details>
oscar.py CHANGED
@@ -355,7 +355,7 @@ class Oscar(datasets.GeneratorBasedBuilder):
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  current_lines = []
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  for filepath in filepaths:
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  logger.info("generating examples from = %s", filepath)
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- with gzip.open(filepath, "rt") as f:
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  for line in f:
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  if len(line.strip()) > 0:
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  current_lines.append(line)
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  current_lines = []
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  for filepath in filepaths:
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  logger.info("generating examples from = %s", filepath)
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+ with gzip.open(filepath, "rt", encoding="utf-8") as f:
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  for line in f:
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  if len(line.strip()) > 0:
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  current_lines.append(line)