id
stringlengths 2
115
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bool 1
class | tags
list | description
stringlengths 0
5.93k
⌀ | downloads
int64 0
1.14M
| likes
int64 0
1.79k
|
|---|---|---|---|---|---|
leiping/teeee | false | [] | null | 0 | 0 |
leoapolonio/AMI_Meeting_Corpus | false | [] | null | 2 | 0 |
leonadase/fdner | false | [] | 用于故障诊断领域相关知识的命名实体识别语料 | 0 | 0 |
leonadase/mycoll3 | false | [] | \
The shared task of CoNLL-2003 concerns language-independent named entity recognition. We will concentrate on
four types of named entities: persons, locations, organizations and names of miscellaneous entities that do
not belong to the previous three groups.
The CoNLL-2003 shared task data files contain four columns separated by a single space. Each word has been put on
a separate line and there is an empty line after each sentence. The first item on each line is a word, the second
a part-of-speech (POS) tag, the third a syntactic chunk tag and the fourth the named entity tag. The chunk tags
and the named entity tags have the format I-TYPE which means that the word is inside a phrase of type TYPE. Only
if two phrases of the same type immediately follow each other, the first word of the second phrase will have tag
B-TYPE to show that it starts a new phrase. A word with tag O is not part of a phrase. Note the dataset uses IOB2
tagging scheme, whereas the original dataset uses IOB1.
For more details see https://www.clips.uantwerpen.be/conll2003/ner/ and https://www.aclweb.org/anthology/W03-0419 | 0 | 0 |
lewtun/asr-preds-test | false | [
"benchmark:superb"
] | null | 0 | 0 |
lewtun/asr_dummy | false | [] | Self-supervised learning (SSL) has proven vital for advancing research in
natural language processing (NLP) and computer vision (CV). The paradigm
pretrains a shared model on large volumes of unlabeled data and achieves
state-of-the-art (SOTA) for various tasks with minimal adaptation. However, the
speech processing community lacks a similar setup to systematically explore the
paradigm. To bridge this gap, we introduce Speech processing Universal
PERformance Benchmark (SUPERB). SUPERB is a leaderboard to benchmark the
performance of a shared model across a wide range of speech processing tasks
with minimal architecture changes and labeled data. Among multiple usages of the
shared model, we especially focus on extracting the representation learned from
SSL due to its preferable re-usability. We present a simple framework to solve
SUPERB tasks by learning task-specialized lightweight prediction heads on top of
the frozen shared model. Our results demonstrate that the framework is promising
as SSL representations show competitive generalizability and accessibility
across SUPERB tasks. We release SUPERB as a challenge with a leaderboard and a
benchmark toolkit to fuel the research in representation learning and general
speech processing.
Note that in order to limit the required storage for preparing this dataset, the
audio is stored in the .flac format and is not converted to a float32 array. To
convert, the audio file to a float32 array, please make use of the `.map()`
function as follows:
```python
import soundfile as sf
def map_to_array(batch):
speech_array, _ = sf.read(batch["file"])
batch["speech"] = speech_array
return batch
dataset = dataset.map(map_to_array, remove_columns=["file"])
``` | 66 | 0 |
lewtun/benchmark-test | false | [] | null | 0 | 0 |
lewtun/binary_classification_dummy | false | [] | null | 0 | 0 |
lewtun/bulk-superb-s3p-superb-49606 | false | [
"benchmark:superb"
] | null | 0 | 1 |
lewtun/drug-reviews | false | [] | null | 6 | 4 |
lewtun/gem-multi-dataset-predictions | false | [] | null | 0 | 0 |
lewtun/gem-sub-03 | false | [
"benchmark:gem"
] | null | 0 | 0 |
lewtun/gem-test-predictions | false | [] | null | 0 | 0 |
lewtun/gem-test-references | false | [] | null | 0 | 0 |
lewtun/github-issues-test | false | [] | null | 0 | 0 |
lewtun/github-issues | false | [
"arxiv:2005.00614"
] | null | 448 | 4 |
lewtun/mnist-preds | false | [
"benchmark:test"
] | This new dataset is designed to solve this great NLP task and is crafted with a lot of care. | 0 | 0 |
lewtun/my-awesome-dataset | false | [
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"language:en",
"license:apache-2.0"
] | null | 0 | 0 |
lewtun/s3prl-sd-dummy | false | [] | null | 0 | 0 |
lewtun/test | false | [] | null | 0 | 0 |
lewtun/text_classification_dummy | false | [] | null | 1 | 0 |
lgrobol/openminuscule | false | [
"task_categories:text-generation",
"task_ids:language-modeling",
"language_creators:crowdsourced",
"multilinguality:multilingual",
"size_categories:100k<n<1M",
"source_datasets:original",
"language:en",
"language:fr",
"license:cc-by-4.0"
] | null | 6 | 0 |
lhoestq/conll2003 | false | [] | null | 5 | 0 |
lhoestq/custom_squad | false | [
"task_categories:question-answering",
"task_ids:extractive-qa",
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:extended|wikipedia",
"language:en",
"license:cc-by-4.0",
"arxiv:1606.05250"
] | Stanford Question Answering Dataset (SQuAD) is a reading comprehension dataset, consisting of questions posed by crowdworkers on a set of Wikipedia articles, where the answer to every question is a segment of text, or span, from the corresponding reading passage, or the question might be unanswerable. | 13 | 0 |
lhoestq/demo1 | false | [] | null | 4,491 | 0 |
lhoestq/squad | false | [] | Stanford Question Answering Dataset (SQuAD) is a reading comprehension dataset, consisting of questions posed by crowdworkers on a set of Wikipedia articles, where the answer to every question is a segment of text, or span, from the corresponding reading passage, or the question might be unanswerable. | 0 | 0 |
lhoestq/test | false | [
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:n<1K",
"source_datasets:original",
"language:en",
"license:mit"
] | This is a test dataset. | 185 | 0 |
lhoestq/test2 | false | [] | null | 0 | 0 |
lhoestq/test_commit_descriptions | false | [] | null | 0 | 0 |
lhoestq/test_zip_txt | false | [] | null | 0 | 0 |
lhoestq/wikipedia_bn | false | [] | Bengali Wikipedia from the dump of 03/20/2021.
The data was processed using the huggingface datasets wikipedia script early april 2021.
The dataset was built from the Wikipedia dump (https://dumps.wikimedia.org/).
Each example contains the content of one full Wikipedia article with cleaning to strip
markdown and unwanted sections (references, etc.). | 0 | 0 |
liam168/nlp_c4_sentiment | false | [] | null | 0 | 0 |
lidia/202111 | false | [] | null | 0 | 0 |
lijingxin/github-issues | false | [] | null | 0 | 0 |
lijingxin/squad_zen | false | [] | null | 14 | 1 |
lijingxin/squad_zh_1 | false | [] | null | 0 | 1 |
limjiayi/hateful_memes_expanded | false | [] | null | 1 | 0 |
lincoln/newsquadfr | false | [
"task_categories:question-answering",
"task_ids:extractive-qa",
"task_ids:open-domain-qa",
"annotations_creators:private",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"source_datasets:newspaper",
"source_datasets:online",
"language:fr-FR",
"license:cc-by-nc-sa-4.0"
] | null | 0 | 2 |
linhd-postdata/pulpo | false | [] | null | 77 | 0 |
linhd-postdata/stanzas | false | [] | Stanzas | 0 | 0 |
liweili/c4_200m | false | [
"task_categories:text-generation",
"source_datasets:allenai/c4",
"language:en",
"grammatical-error-correction"
] | \
GEC Dataset Generated from C4 | 62 | 12 |
lkarjun/Malayalam-Articles | false | [] | null | 0 | 0 |
lkiouiou/o9ui7877687 | false | [] | null | 0 | 0 |
lkndsjkndgskjngkjsndkj/jsjdjsdvkjvszlhdskb | false | [] | null | 0 | 0 |
llangnickel/long-covid-classification-data | false | [
"task_categories:text-classification",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:unknown",
"source_datasets:original",
"language:en",
"license:cc-by-4.0"
] | null | 22 | 0 |
lohanna/testedjkcxkf | false | [] | null | 0 | 0 |
loretoparisi/spoken-punctuation | false | [] | null | 0 | 1 |
lorsorlah/Dadedadedam | false | [] | null | 0 | 0 |
loveguruji609/dfdfsdfsdfsdfsdfsd | false | [] | null | 0 | 0 |
lpsc-fiuba/melisa | false | [
"task_categories:text-classification",
"task_ids:language-modeling",
"task_ids:sentiment-classification",
"task_ids:sentiment-scoring",
"task_ids:topic-classification",
"annotations_creators:found",
"language_creators:found",
"source_datasets:original",
"language:es",
"language:pt",
"license:other"
] | null | 0 | 2 |
lsb/ancient-latin-passages | false | [
"license:agpl-3.0"
] | null | 0 | 0 |
lsb/million-english-numbers | false | [
"arxiv:1803.09010"
] | null | 0 | 0 |
lucien/sciencemission | false | [] | null | 0 | 0 |
lucien/voacantonesed | false | [] | null | 0 | 0 |
lucien/wsaderfffjjjhhh | false | [] | null | 0 | 0 |
lucio/common_voice_eval | false | [] | null | 0 | 0 |
lukasmasuch/my-test-repo-3 | false | [] | null | 0 | 0 |
lukasmasuch/my-test-repo-4 | false | [] | null | 0 | 0 |
lukasmasuch/test-2 | false | [] | null | 0 | 0 |
lukasmasuch/test-3 | false | [] | null | 0 | 0 |
lukasmasuch/test | false | [] | null | 0 | 0 |
lukesjordan/worldbank-project-documents | false | [
"task_categories:table-to-text",
"task_categories:question-answering",
"task_categories:summarization",
"task_categories:text-generation",
"task_ids:abstractive-qa",
"task_ids:closed-domain-qa",
"task_ids:extractive-qa",
"task_ids:language-modeling",
"task_ids:named-entity-recognition",
"task_ids:text-simplification",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:unknown",
"source_datasets:original",
"language:en",
"license:other",
"conditional-text-generation",
"structure-prediction"
] | null | 10 | 1 |
luketheduke/stsb | false | [] | null | 0 | 0 |
luofengge/mydata | false | [] | null | 0 | 0 |
luofengge/testDataset | false | [] | null | 0 | 0 |
luomingshuang/GRID_audio | false | [] | null | 0 | 0 |
luomingshuang/GRID_text | false | [] | null | 0 | 0 |
luomingshuang/grid_lip_160_80 | false | [] | null | 0 | 0 |
luozhouyang/dureader | false | [] | null | 30 | 3 |
luozhouyang/kgclue-knowledge | false | [] | null | 0 | 0 |
luozhouyang/question-answering-datasets | false | [] | null | 4 | 0 |
lvwerra/abc-test | false | [] | null | 0 | 0 |
lvwerra/abc | false | [] | null | 0 | 0 |
codeparrot/codeparrot-clean-train | false | [] | null | 753 | 6 |
codeparrot/codeparrot-clean-valid | false | [] | null | 656 | 3 |
codeparrot/codeparrot-clean | false | [
"python",
"code"
] | null | 224 | 23 |
lvwerra/codeparrot-valid-clean-minimal | false | [] | null | 22 | 0 |
lvwerra/codeparrot-valid | false | [] | null | 1 | 0 |
lvwerra/github-alphacode | false | [] | null | 3 | 0 |
codeparrot/github-code | false | [
"task_categories:text-generation",
"task_ids:language-modeling",
"language_creators:crowdsourced",
"language_creators:expert-generated",
"multilinguality:multilingual",
"size_categories:unknown",
"language:code",
"license:other"
] | The GitHub Code dataest consists of 115M code files from GitHub in 32 programming languages with 60 extensions totalling in 1TB of text data. The dataset was created from the GitHub dataset on BiqQuery. | 1,240 | 86 |
lvwerra/important_dataset | false | [] | null | 0 | 0 |
lvwerra/lm_ar_wikipedia | false | [] | null | 0 | 0 |
lvwerra/red-wine | false | [] | null | 0 | 2 |
lvwerra/repo-images | false | [] | null | 0 | 0 |
lvwerra/test | false | [] | null | 0 | 0 |
lysandre/image-to-text | false | [] | null | 0 | 0 |
lysandre/my-cool-dataset | false | [] | null | 0 | 0 |
m3hrdadfi/recipe_nlg_lite | false | [] | RecipeNLG: A Cooking Recipes Dataset for Semi-Structured Text Generation - Lite version
The dataset we publish contains 7,198 cooking recipes (>7K).
It's processed in more careful way and provides more samples than any other dataset in the area. | 4 | 1 |
mad/IndonesiaNewsDataset | false | [] | null | 0 | 0 |
maindadwitiya/weather_dataset | false | [] | null | 2 | 0 |
maji/npo_mission_statement_ucf | false | [] | null | 0 | 0 |
majod/CleanNaturalQuestionsDataset | false | [] | null | 0 | 0 |
makanan/umich | false | [] | null | 0 | 0 |
malay-huggingface/pembalakan | false | [] | null | 0 | 0 |
mammut/mammut-corpus-venezuela-test-set | false | [
"task_ids:language-modeling",
"annotations_creators:no-annotation",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:unknown",
"source_datasets:original",
"language:es",
"license:cc-by-nc-nd-4.0"
] | null | 0 | 0 |
mammut/mammut-corpus-venezuela | false | [
"task_ids:language-modeling",
"annotations_creators:no-annotation",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:unknown",
"source_datasets:original",
"language:es",
"license:cc-by-nc-nd-4.0"
] | null | 0 | 0 |
manifoldix/sg_testset_fhnw | false | [] | null | 0 | 0 |
manifoldix/swg_parliament_fhnw | false | [] | null | 0 | 0 |
manishk31/Demo | false | [] | null | 0 | 0 |
manu/fr_corpora_parliament_processed-lowercased | false | [] | null | 0 | 0 |
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