sha stringlengths 40 40 | text stringlengths 1 13.4M | id stringlengths 2 117 | tags listlengths 1 7.91k | created_at stringlengths 25 25 | metadata stringlengths 2 875k | last_modified stringlengths 25 25 | arxiv listlengths 0 25 | languages listlengths 0 7.91k | tags_str stringlengths 17 159k | text_str stringlengths 1 447k | text_lists listlengths 0 352 | processed_texts listlengths 1 353 | tokens_length listlengths 1 353 | input_texts listlengths 1 40 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
8950f534f8012eef317e1b90b2a8b13fbec8746d |
# Dataset Card for GAD
## Dataset Description
- **Homepage:** https://geneticassociationdb.nih.gov/
- **Pubmed:** True
- **Public:** True
- **Tasks:** TXTCLASS
A corpus identifying associations between genes and diseases by a semi-automatic
annotation procedure based on the Genetic Association Database.
## Note ... | bigbio/gad | [
"multilinguality:momolingual",
"language:en",
"license:cc-by-4.0",
"region:us"
] | 2022-09-26T02:36:32+00:00 | {"language": ["en"], "license": "cc-by-4.0", "multilinguality": "momolingual", "paperswithcode_id": "gad", "pretty_name": "GAD", "bigbio_language": ["English"], "bigbio_license_shortname": "CC_BY_4p0", "homepage": "https://geneticassociationdb.nih.gov/", "bigbio_pubmed": true, "bigbio_public": true, "bigbio_tasks": ["T... | 2022-12-22T15:25:28+00:00 | [] | [
"en"
] | TAGS
#multilinguality-momolingual #language-English #license-cc-by-4.0 #region-us
|
# Dataset Card for GAD
## Dataset Description
- Homepage: URL
- Pubmed: True
- Public: True
- Tasks: TXTCLASS
A corpus identifying associations between genes and diseases by a semi-automatic
annotation procedure based on the Genetic Association Database.
## Note about homepage
The homepage for this dataset is n... | [
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e0ca639ce1a5f1267ada3f8fae2fdad79737887c |
# Dataset Card for BioASQ Task B
## Dataset Description
- **Homepage:** http://participants-area.bioasq.org/datasets/
- **Pubmed:** True
- **Public:** False
- **Tasks:** QA
The BioASQ corpus contains multiple question
answering tasks annotated by biomedical experts, including yes/no, factoid, list,
and summary qu... | bigbio/bioasq_task_b | [
"multilinguality:monolingual",
"language:en",
"license:other",
"region:us"
] | 2022-09-26T03:05:28+00:00 | {"language": ["en"], "license": "other", "multilinguality": "monolingual", "pretty_name": "BioASQ Task B", "bigbio_language": ["English"], "bigbio_license_shortname": "NLM_LICENSE", "homepage": "http://participants-area.bioasq.org/datasets/", "bigbio_pubmed": true, "bigbio_public": false, "bigbio_tasks": ["QUESTION_ANS... | 2022-12-22T15:41:12+00:00 | [] | [
"en"
] | TAGS
#multilinguality-monolingual #language-English #license-other #region-us
|
# Dataset Card for BioASQ Task B
## Dataset Description
- Homepage: URL
- Pubmed: True
- Public: False
- Tasks: QA
The BioASQ corpus contains multiple question
answering tasks annotated by biomedical experts, including yes/no, factoid, list,
and summary questions. Pertaining to our objective of comparing neural l... | [
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7f2fb24be7c82a385ee81a1152bc679b6400f41b |  | VirtualJesus/Anthonyface | [
"region:us"
] | 2022-09-26T04:01:42+00:00 | {} | 2022-09-26T07:48:44+00:00 | [] | [] | TAGS
#region-us
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2be31cb9f5880cbce04b5b68299121992587ace7 | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: Samuel-Fipps/t5-efficient-large-nl36_fine_tune_sum_V2
* Dataset: samsum
* Config: samsum
* Split: test
To run... | autoevaluate/autoeval-eval-samsum-samsum-8a4c42-1554855493 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-09-26T05:54:54+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["samsum"], "eval_info": {"task": "summarization", "model": "Samuel-Fipps/t5-efficient-large-nl36_fine_tune_sum_V2", "metrics": ["mse"], "dataset_name": "samsum", "dataset_config": "samsum", "dataset_split": "test", "col_mapping": {"text": "dialog... | 2022-09-26T06:02:52+00:00 | [] | [] | TAGS
#autotrain #evaluation #region-us
| # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: Samuel-Fipps/t5-efficient-large-nl36_fine_tune_sum_V2
* Dataset: samsum
* Config: samsum
* Split: test
To run new evaluation jobs, visit Hugging ... | [
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a35672081af08bf55b7cdcdd8f2864edcb50a2ff | train data | BraimComplexe/train_1 | [
"region:us"
] | 2022-09-26T08:02:31+00:00 | {} | 2022-09-26T08:13:22+00:00 | [] | [] | TAGS
#region-us
| train data | [] | [
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911e1d214162fd11d2c78d3f1428cbfcbe07782c |
# Dataset Card for MultiLegalPile: A Large-Scale Multilingual Corpus for the Legal Domain
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
... | joelniklaus/Multi_Legal_Pile | [
"task_categories:fill-mask",
"annotations_creators:other",
"language_creators:found",
"multilinguality:multilingual",
"size_categories:10M<n<100M",
"source_datasets:original",
"language:bg",
"language:cs",
"language:da",
"language:de",
"language:el",
"language:en",
"language:es",
"language... | 2022-09-26T09:28:06+00:00 | {"annotations_creators": ["other"], "language_creators": ["found"], "language": ["bg", "cs", "da", "de", "el", "en", "es", "et", "fi", "fr", "ga", "hr", "hu", "it", "lt", "lv", "mt", "nl", "pl", "pt", "ro", "sk", "sl", "sv"], "license": ["cc-by-nc-sa-4.0"], "multilinguality": ["multilingual"], "size_categories": ["10M<... | 2024-01-12T08:50:24+00:00 | [
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#task_categories-fill-mask #annotations_creators-other #language_creators-found #multilinguality-multilingual #size_categories-10M<n<100M #source_datasets-original #language-Bulgarian #language-Czech #language-Danish #language-German #language-Modern Greek (1453-) #language-English #language-Spanish #language-Esto... | Dataset Card for MultiLegalPile: A Large-Scale Multilingual Corpus for the Legal Domain
=======================================================================================
Table of Contents
-----------------
* Table of Contents
* Dataset Description
+ Dataset Summary
+ Supported Tasks and Leaderboards
+ Lang... | [
"### Dataset Summary\n\n\nThe Multi\\_Legal\\_Pile is a large-scale multilingual legal dataset suited for pretraining language models.\nIt spans over 24 languages and five legal text types.",
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db3f9a34f0c1c287db91e86861ca8bdff67f5935 |
# Download zenodo dataset files using huggingface datasets
You can download a specific file from the Zenodo dataset using the following code:
Zenodo id : 5172018
File name : FDB-17-fragmentset.smi.gz
```python
from datasets import load_dataset
load_dataset("osbm/zenodo", "5172018_FDB-17-fragmentset.smi.gz")
```
Th... | osbm/zenodo | [
"region:us"
] | 2022-09-26T10:04:40+00:00 | {"pretty_name": "Download Zenodo Dataset files"} | 2023-06-12T10:36:45+00:00 | [] | [] | TAGS
#region-us
|
# Download zenodo dataset files using huggingface datasets
You can download a specific file from the Zenodo dataset using the following code:
Zenodo id : 5172018
File name : URL
This command will also copy the file into your current directory so that you can use it directly.
Here is an example notebook: URL
# ... | [
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05f2b9a2b864e04ec1a969f6d31923a776307c53 | ........ | datascopum/datascopum | [
"region:us"
] | 2022-09-26T13:56:42+00:00 | {} | 2022-09-29T15:33:40+00:00 | [] | [] | TAGS
#region-us
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68d75d195c960726ab362a157dfa311e075295a8 | # Dataset Card for "model-repos-stats"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | open-source-metrics/model-repos-stats | [
"region:us"
] | 2022-09-26T14:54:28+00:00 | {"dataset_info": {"features": [{"name": "Unnamed: 0", "dtype": "int64"}, {"name": "repo_id", "dtype": "string"}, {"name": "author", "dtype": "string"}, {"name": "model_type", "dtype": "string"}, {"name": "files_per_repo", "dtype": "int64"}, {"name": "downloads_30d", "dtype": "int64"}, {"name": "library", "dtype": "stri... | 2023-07-03T00:35:17+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "model-repos-stats"
More Information needed | [
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da31b6c38403a4811b20342486bdf0ec2a724a2a | **Context**
Generating humor is a complex task in the domain of machine learning, and it requires the models to understand the deep semantic meaning of a joke in order to generate new ones. Such problems, however, are difficult to solve due to a number of reasons, one of which is the lack of a database that gives an e... | ysharma/short_jokes | [
"license:mit",
"region:us"
] | 2022-09-26T15:57:00+00:00 | {"license": "mit"} | 2022-09-26T16:11:06+00:00 | [] | [] | TAGS
#license-mit #region-us
| Context
Generating humor is a complex task in the domain of machine learning, and it requires the models to understand the deep semantic meaning of a joke in order to generate new ones. Such problems, however, are difficult to solve due to a number of reasons, one of which is the lack of a database that gives an elabo... | [] | [
"TAGS\n#license-mit #region-us \n"
] | [
11
] | [
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de93f205b1d46c99e45e3da694207776da2bbf63 |
# Dataset Card for CoSimLex
### Dataset Summary
The dataset contains human similarity ratings for pairs of words. The annotators were presented with contexts that contained both of the words in the pair and the dataset features two different contexts per pair. The words were sourced from the English, Croatian, Finni... | cjvt/cosimlex | [
"task_categories:other",
"annotations_creators:crowdsourced",
"language_creators:found",
"multilinguality:multilingual",
"size_categories:n<1K",
"language:en",
"language:hr",
"language:sl",
"language:fi",
"license:gpl-3.0",
"graded-word-similarity-in-context",
"region:us"
] | 2022-09-26T17:13:05+00:00 | {"annotations_creators": ["crowdsourced"], "language_creators": ["found"], "language": ["en", "hr", "sl", "fi"], "license": ["gpl-3.0"], "multilinguality": ["multilingual"], "size_categories": ["n<1K"], "source_datasets": [], "task_categories": ["other"], "task_ids": [], "pretty_name": "CoSimLex", "tags": ["graded-word... | 2022-10-21T06:34:58+00:00 | [] | [
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] | TAGS
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|
# Dataset Card for CoSimLex
### Dataset Summary
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16e24521436eaf961e62b0406744617666a741ba |
# Dataset Card for Airplane Crashes and Fatalities
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Struc... | nateraw/airplane-crashes-and-fatalities | [
"license:cc-by-nc-sa-4.0",
"region:us"
] | 2022-09-26T18:02:55+00:00 | {"license": ["cc-by-nc-sa-4.0"], "converted_from": "kaggle", "kaggle_id": "thedevastator/airplane-crashes-and-fatalities"} | 2022-09-27T16:55:18+00:00 | [] | [] | TAGS
#license-cc-by-nc-sa-4.0 #region-us
|
# Dataset Card for Airplane Crashes and Fatalities
## Table of Contents
- Table of Contents
- Dataset Description
- Dataset Summary
- Supported Tasks and Leaderboards
- Languages
- Dataset Structure
- Data Instances
- Data Fields
- Data Splits
- Dataset Creation
- Curation Rationale
- Source Data
- ... | [
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ad5e82960d05d634773914859e9e47c70614823c | Simple English Wikipedia it has only about 170k articles. We split these articles into paragraphs.
wikipedia_filepath = 'simplewiki-2020-11-01.jsonl.gz'
if not os.path.exists(wikipedia_filepath):
util.http_get('http://sbert.net/datasets/simplewiki-2020-11-01.jsonl.gz', wikipedia_filepath) | gfhayworth/wiki_mini | [
"region:us"
] | 2022-09-26T19:42:59+00:00 | {} | 2023-01-28T23:28:54+00:00 | [] | [] | TAGS
#region-us
| Simple English Wikipedia it has only about 170k articles. We split these articles into paragraphs.
wikipedia_filepath = 'URL'
if not URL(wikipedia_filepath):
util.http_get('URL wikipedia_filepath) | [] | [
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] | [
6
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d4548d8a0d713c364d69e6dafeec59d3c7717026 | Tweets containing '#Mets' from early August through late September | Ceetar/MetsTweets | [
"region:us"
] | 2022-09-26T22:22:51+00:00 | {} | 2022-09-26T23:08:51+00:00 | [] | [] | TAGS
#region-us
| Tweets containing '#Mets' from early August through late September | [] | [
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] | [
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5e26419ab91ed4a212eb945097dfc3b5d0687401 | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: Tristan/opt-66b-copy
* Dataset: mathemakitten/winobias_antistereotype_dev
* Config: mathemakit... | autoevaluate/autoeval-eval-mathemakitten__winobias_antistereotype_dev-mathemakitte-08a58b-1563555688 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-09-27T00:44:58+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["mathemakitten/winobias_antistereotype_dev"], "eval_info": {"task": "text_zero_shot_classification", "model": "Tristan/opt-66b-copy", "metrics": [], "dataset_name": "mathemakitten/winobias_antistereotype_dev", "dataset_config": "mathemakitten--wi... | 2022-09-27T03:26:16+00:00 | [] | [] | TAGS
#autotrain #evaluation #region-us
| # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: Tristan/opt-66b-copy
* Dataset: mathemakitten/winobias_antistereotype_dev
* Config: mathemakitten--winobias_antistereotype_dev
* S... | [
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5bf51cd1b371b4c8aa0fe48d64123e20b25cdaf7 |
# Aggregated Captcha Images and Text
## Credits
All the images (not the texts) here contained have been downloaded and selected from various datasets on kaggle.com
### What is this?
This is a dataset containing some hundreds of thousands of images taken from real and used captchas (reCaptcha, hCaptcha and various ... | tcsenpai/aggregated_captcha_images_and_text | [
"license:cc-by-nc-4.0",
"region:us"
] | 2022-09-27T01:36:22+00:00 | {"license": "cc-by-nc-4.0"} | 2022-09-27T02:31:17+00:00 | [] | [] | TAGS
#license-cc-by-nc-4.0 #region-us
|
# Aggregated Captcha Images and Text
## Credits
All the images (not the texts) here contained have been downloaded and selected from various datasets on URL
### What is this?
This is a dataset containing some hundreds of thousands of images taken from real and used captchas (reCaptcha, hCaptcha and various others)... | [
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76aeb129b64a67d72998420da80c2e51032c6907 |
# Dataset Card for Lexicap
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
-... | shubhamg2208/lexicap | [
"task_categories:text-classification",
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"karpa... | 2022-09-27T02:59:08+00:00 | {"language_creators": ["found"], "language": ["en"], "license": [], "multilinguality": ["monolingual"], "size_categories": ["n<1K"], "source_datasets": ["original"], "task_categories": ["text-classification", "text-generation"], "task_ids": ["sentiment-analysis", "dialogue-modeling", "language-modeling"], "pretty_name"... | 2022-09-27T03:41:00+00:00 | [] | [
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|
# Dataset Card for Lexicap
## Table of Contents
- Dataset Description
- Dataset Summary
- Supported Tasks and Leaderboards
- Languages
- Dataset Structure
- Data Instances
- Data Fields
- Data Splits
- Dataset Creation
- Curation Rationale
- Source Data
- Annotations
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d5dfe0d2fdc72e5d881a47cd3e8e8e57c2ca5b1b | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: pszemraj/long-t5-tglobal-large-pubmed-3k-booksum-16384-WIP17
* Dataset: kmfoda/booksum
* Config: kmfoda--books... | autoevaluate/autoeval-eval-kmfoda__booksum-kmfoda__booksum-ba6080-1564655701 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-09-27T07:14:27+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["kmfoda/booksum"], "eval_info": {"task": "summarization", "model": "pszemraj/long-t5-tglobal-large-pubmed-3k-booksum-16384-WIP17", "metrics": [], "dataset_name": "kmfoda/booksum", "dataset_config": "kmfoda--booksum", "dataset_split": "test", "col... | 2022-09-28T11:45:02+00:00 | [] | [] | TAGS
#autotrain #evaluation #region-us
| # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: pszemraj/long-t5-tglobal-large-pubmed-3k-booksum-16384-WIP17
* Dataset: kmfoda/booksum
* Config: kmfoda--booksum
* Split: test
To run new evaluat... | [
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5b001451c8a86ecabf3e8aa1486ab7780534b48a | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: pszemraj/long-t5-tglobal-large-pubmed-3k-booksum-16384-WIP17
* Dataset: billsum
* Config: default
* Split: tes... | autoevaluate/autoeval-eval-billsum-default-37bdaa-1564755702 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-09-27T07:14:31+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["billsum"], "eval_info": {"task": "summarization", "model": "pszemraj/long-t5-tglobal-large-pubmed-3k-booksum-16384-WIP17", "metrics": [], "dataset_name": "billsum", "dataset_config": "default", "dataset_split": "test", "col_mapping": {"text": "t... | 2022-09-28T13:20:08+00:00 | [] | [] | TAGS
#autotrain #evaluation #region-us
| # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: pszemraj/long-t5-tglobal-large-pubmed-3k-booksum-16384-WIP17
* Dataset: billsum
* Config: default
* Split: test
To run new evaluation jobs, visit... | [
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ee5cf7dc24900b58bd4a0f8c0de335ad4f7bdb4d | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: pszemraj/long-t5-tglobal-large-pubmed-3k-booksum-16384-WIP17
* Dataset: launch/gov_report
* Config: plain_text... | autoevaluate/autoeval-eval-launch__gov_report-plain_text-45e121-1564955705 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-09-27T07:14:49+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["launch/gov_report"], "eval_info": {"task": "summarization", "model": "pszemraj/long-t5-tglobal-large-pubmed-3k-booksum-16384-WIP17", "metrics": [], "dataset_name": "launch/gov_report", "dataset_config": "plain_text", "dataset_split": "test", "co... | 2022-09-27T22:02:40+00:00 | [] | [] | TAGS
#autotrain #evaluation #region-us
| # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: pszemraj/long-t5-tglobal-large-pubmed-3k-booksum-16384-WIP17
* Dataset: launch/gov_report
* Config: plain_text
* Split: test
To run new evaluatio... | [
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b080eb0ef952f2c8283f6bf0186d2e03bf88b527 | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: pszemraj/long-t5-tglobal-large-pubmed-3k-booksum-16384-WIP15
* Dataset: launch/gov_report
* Config: plain_text... | autoevaluate/autoeval-eval-launch__gov_report-plain_text-45e121-1564955706 | [
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#autotrain #evaluation #region-us
| # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: pszemraj/long-t5-tglobal-large-pubmed-3k-booksum-16384-WIP15
* Dataset: launch/gov_report
* Config: plain_text
* Split: test
To run new evaluatio... | [
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702c3ff0bee31d2479f7f98a1095210683c3fec0 | #### automatic-dissection
# **HuBMAP + HPA - Hacking the Human Body**
##### **Segment multi-organ functional tissue units in biopsy slides from several different organs.**
### **Overview**
When you think of "life hacks," normally you’d imagine productivity techniques. But how about the kind that helps you understan... | n1ghtf4l1/automatic-dissection | [
"license:mit",
"region:us"
] | 2022-09-27T08:45:43+00:00 | {"license": "mit"} | 2022-11-01T07:08:47+00:00 | [] | [] | TAGS
#license-mit #region-us
| #### automatic-dissection
# HuBMAP + HPA - Hacking the Human Body
##### Segment multi-organ functional tissue units in biopsy slides from several different organs.
### Overview
When you think of "life hacks," normally you’d imagine productivity techniques. But how about the kind that helps you understand your body ... | [
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3b0559e997b2dc1a5eb080364ba2420e29e4dd2d |
Converted to json version of dataset from [Koziev/NLP_Datasets](https://github.com/Koziev/NLP_Datasets/blob/master/Conversations/Data/extract_dialogues_from_anekdots.tar.xz) | artemsnegirev/dialogs_from_jokes | [
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"region:us"
] | 2022-09-27T10:32:40+00:00 | {"language": ["ru"], "license": "cc0-1.0", "multilinguality": ["monolingual"], "size_categories": ["100K<n<1M"], "task_categories": ["conversational"], "task_ids": ["dialogue-generation"], "pretty_name": "Dialogs from Jokes"} | 2022-09-27T10:43:32+00:00 | [] | [
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5500a07ad0e88dae61f0f78a46f17751d5a95c7f |
```sh
git clone https://github.com/rust-bio/rust-bio-tools
rm -f RustBioGPT-validate.csv && for i in `find . -name "*.rs"`;do paste -d "," <(echo "rust-bio-tools"|perl -pe "s/(.+)/\"\1\"/g") <(echo $i|perl -pe "s/(.+)/\"\1\"/g") <(perl -pe "s/\n/\\\n/g" $i|perl -pe s"/\"/\'/g" |perl -pe "s/(.+)/\"\1\"/g") <(echo "mit... | jelber2/RustBioGPT-valid | [
"license:mit",
"region:us"
] | 2022-09-27T10:52:42+00:00 | {"license": "mit"} | 2022-09-27T11:01:37+00:00 | [] | [] | TAGS
#license-mit #region-us
| [] | [
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58684b7a75ae57ed0dbcfcb87bdbd8ff3541aade |
# laion2B-multi-chinese-subset
- Github: [Fengshenbang-LM](https://github.com/IDEA-CCNL/Fengshenbang-LM)
- Docs: [Fengshenbang-Docs](https://fengshenbang-doc.readthedocs.io/)
## 简介 Brief Introduction
取自Laion2B多语言多模态数据集中的中文部分，一共143M个图文对。
A subset from Laion2B (a multimodal dataset), around 143M image-text pairs (on... | IDEA-CCNL/laion2B-multi-chinese-subset | [
"task_categories:feature-extraction",
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"arxiv:2209.02970",
"region:us"
] | 2022-09-27T11:22:38+00:00 | {"annotations_creators": ["crowdsourced"], "language_creators": ["crowdsourced"], "language": ["zh"], "license": ["cc-by-4.0"], "multilinguality": ["monolingual"], "task_categories": ["feature-extraction"], "pretty_name": "laion2B-multi-chinese-subset"} | 2023-04-06T05:32:18+00:00 | [
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|
# laion2B-multi-chinese-subset
- Github: Fengshenbang-LM
- Docs: Fengshenbang-Docs
## 简介 Brief Introduction
取自Laion2B多语言多模态数据集中的中文部分，一共143M个图文对。
A subset from Laion2B (a multimodal dataset), around 143M image-text pairs (only Chinese).
## 数据集信息 Dataset Information
大约一共143M个中文图文对。大约占用19GB空间（仅仅是url等文本信息，不包含图片）。
-... | [
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4d17ebae87690692e4ce9f102f35d28fa7ed5b66 |
# Dataset Card for WinoGAViL
- [Dataset Description](#dataset-description)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Colab notebook code for Winogavil evaluation with CLIP](#colab-notebook-code-for-winogavil-evaluation-with-clip)
- [Languages](#languages)
- [Dataset Structure](#... | severo/winogavil | [
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# Dataset Card for WinoGAViL
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c20fb7cdff2c4b197e4c4125f850db01a559b4ab | Dataset for paper: Learning the Solution Operator of Boundary Value Problems using Graph Neural Networks
https://arxiv.org/abs/2206.14092 | winfried/gnn_bvp_solver | [
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| Dataset for paper: Learning the Solution Operator of Boundary Value Problems using Graph Neural Networks
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c219307f7fd35f295dcd0cdf4cc94cd949158b30 | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-6.7b
* Dataset: mathemakitten/winobias_antistereotype_dev
* Config: mathemakitten... | autoevaluate/autoeval-eval-mathemakitten__winobias_antistereotype_dev-mathemakitte-7776e8-1573055858 | [
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| # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
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4596f8cd06aa6f0fc71957d2e6a1f33c8664b643 | # Dataset Card for AutoTrain Evaluator
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fba43e6d568abcfdab87ffe3068571fd21dca450 | # Dataset Card for AutoTrain Evaluator
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25a3771e345e9226611b04bc2bd695eaebad972e | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
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36506bf4050ad3043e111c1812be9c557b238954 | # Dataset Card for AutoTrain Evaluator
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2afaf26908533ee079a8fe1fb7d36c595b8d7176 | # Dataset Card for AutoTrain Evaluator
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e17a8195959cef8071410fd7fa8c4130a16a3a72 |
# Dataset Card for "tner/wikiann"
## Dataset Description
- **Repository:** [T-NER](https://github.com/asahi417/tner)
- **Paper:** [https://aclanthology.org/P17-1178/](https://aclanthology.org/P17-1178/)
- **Dataset:** WikiAnn
- **Domain:** Wikipedia
- **Number of Entity:** 3
### Dataset Summary
WikiAnn NER dataset... | tner/wikiann | [
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===============================
Dataset Description
-------------------
* Repository: T-NER
* Paper: URL
* Dataset: WikiAnn
* Domain: Wikipedia
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### Dataset Summary
WikiAnn NER dataset formatted in a part of TNER project.
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# Dataset Card for "tner/wikineural"
## Dataset Description
- **Repository:** [T-NER](https://github.com/asahi417/tner)
- **Paper:** [https://aclanthology.org/2021.findings-emnlp.215/](https://aclanthology.org/2021.findings-emnlp.215/)
- **Dataset:** WikiNeural
- **Domain:** Wikipedia
- **Number of Entity:** 16
##... | tner/wikineural | [
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| Dataset Card for "tner/wikineural"
==================================
Dataset Description
-------------------
* Repository: T-NER
* Paper: URL
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* Domain: Wikipedia
* Number of Entity: 16
### Dataset Summary
WikiAnn NER dataset formatted in a part of TNER project.
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3c9285ea8a531da6066ac04bb17394bc8e8ca3b6 | # Dataset Card for "pip"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | open-source-metrics/pip | [
"region:us"
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facdfd1c6f139820e44b5dd7b341d056fbe2044e |
# Dataset Card for "tner/multinerd"
## Dataset Description
- **Repository:** [T-NER](https://github.com/asahi417/tner)
- **Paper:** [https://aclanthology.org/2022.findings-naacl.60/](https://aclanthology.org/2022.findings-naacl.60/)
- **Dataset:** MultiNERD
- **Domain:** Wikipedia, WikiNews
- **Number of Entity:** 1... | tner/multinerd | [
"task_categories:token-classification",
"task_ids:named-entity-recognition",
"multilinguality:multilingual",
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"language:fr",
"language:it",
"language:nl",
"language:pl",
"language:pt",
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"region:us"
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| Dataset Card for "tner/multinerd"
=================================
Dataset Description
-------------------
* Repository: T-NER
* Paper: URL
* Dataset: MultiNERD
* Domain: Wikipedia, WikiNews
* Number of Entity: 18
### Dataset Summary
MultiNERD NER benchmark dataset formatted in a part of TNER project.
* Enti... | [
"### Dataset Summary\n\n\nMultiNERD NER benchmark dataset formatted in a part of TNER project.\n\n\n* Entity Types: 'PER', 'LOC', 'ORG', 'ANIM', 'BIO', 'CEL', 'DIS', 'EVE', 'FOOD', 'INST', 'MEDIA', 'PLANT', 'MYTH', 'TIME', 'VEHI', 'MISC', 'SUPER', 'PHY'\n\n\nDataset Structure\n-----------------",
"### Data Instan... | [
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ebbb3a2ae953c0a73ab3db40e849c6c23a82542a |
---
Sample
---
- 6900 transcripts
- 44 churches
- timeframe: 2010-2022
- Denomination: Unitarian Universalist, USA
---
Dataset structure
---
- church (church name or website)
- source (mp3 file)
- text
- sentences (count)
- errors (number of sentences skipped because could not understand audio, or just long pauses ... | marcmaxmeister/unitarian-universalist-sermons | [
"license:mit",
"region:us"
] | 2022-09-27T21:11:20+00:00 | {"license": "mit"} | 2022-09-28T20:04:16+00:00 | [] | [] | TAGS
#license-mit #region-us
|
---
Sample
---
- 6900 transcripts
- 44 churches
- timeframe: 2010-2022
- Denomination: Unitarian Universalist, USA
---
Dataset structure
---
- church (church name or website)
- source (mp3 file)
- text
- sentences (count)
- errors (number of sentences skipped because could not understand audio, or just long pauses ... | [] | [
"TAGS\n#license-mit #region-us \n"
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11
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6947305648990c358f904def2a18cc3cc62fd4c0 |
The code is provided under a Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license. Under the license, the code is provided royalty free for non-commercial purposes only. The code may be covered by patents and if you want to use the code for commercial purposes, please contact us for a different license.
... | jmercat/risk_biased_dataset | [
"license:cc-by-nc-4.0",
"region:us"
] | 2022-09-27T21:35:21+00:00 | {"license": "cc-by-nc-4.0"} | 2023-08-01T18:08:31+00:00 | [] | [] | TAGS
#license-cc-by-nc-4.0 #region-us
|
The code is provided under a Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license. Under the license, the code is provided royalty free for non-commercial purposes only. The code may be covered by patents and if you want to use the code for commercial purposes, please contact us for a different license.
... | [] | [
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5e92c47f62e3a16dc4b38ed70aa8841eacb22514 | ---
annotations_creators:
- expert-generated
language:
- en
language_creators:
- found
license:
- mit
multilinguality:
- monolingual
paperswithcode_id: acronym-identification
pretty_name: datahogyas
size_categories:
- 10K<n<100K
source_datasets:
- original
tags: []
task_categories:
- token-classification
task_ids:
- pa... | dhruvs00/datahogyas | [
"region:us"
] | 2022-09-28T05:47:21+00:00 | {} | 2022-09-28T07:08:02+00:00 | [] | [] | TAGS
#region-us
| ---
annotations_creators:
- expert-generated
language:
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language_creators:
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license:
- mit
multilinguality:
- monolingual
paperswithcode_id: acronym-identification
pretty_name: datahogyas
size_categories:
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source_datasets:
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tags: []
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5e2a11d9729621f0375b6ccd1114d335c6ee1b94 | # Dummy Dataset for AutoTrain Benchmark
This dataset contains dummy data that's needed to create AutoTrain projects for benchmarks like [RAFT](https://huggingface.co/spaces/ought/raft-leaderboard). See [here](https://github.com/huggingface/hf_benchmarks) for more details. | autoevaluator/benchmark-dummy-data | [
"region:us"
] | 2022-09-28T06:57:08+00:00 | {} | 2022-11-18T13:19:56+00:00 | [] | [] | TAGS
#region-us
| # Dummy Dataset for AutoTrain Benchmark
This dataset contains dummy data that's needed to create AutoTrain projects for benchmarks like RAFT. See here for more details. | [
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519a29f2934a650967d7c6c99f4c53ed99e083d0 | # dureader
数据来自DuReader-Retreval数据集，这里是[原始地址](https://github.com/baidu/DuReader/tree/master/DuReader-Retrieval)。
> 本数据集只用作学术研究使用。如果本仓库涉及侵权行为，会立即删除。
| zyznull/dureader-retrieval-corpus | [
"license:apache-2.0",
"region:us"
] | 2022-09-28T07:03:03+00:00 | {"license": "apache-2.0"} | 2023-01-03T08:05:06+00:00 | [] | [] | TAGS
#license-apache-2.0 #region-us
| # dureader
数据来自DuReader-Retreval数据集，这里是原始地址。
> 本数据集只用作学术研究使用。如果本仓库涉及侵权行为，会立即删除。
| [
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] |
f33c72ade15f98638f3598a9ca4ac989d21f699e |
All eight of datasets in ESC can be downloaded and prepared in just a single line of code through the Hugging Face Datasets library:
```python
from datasets import load_dataset
librispeech = load_dataset("esc-benchmark/esc-datasets", "librispeech", split="train")
```
- `"esc-benchmark"`: the repository namespace. T... | esc-benchmark/esc-datasets | [
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... | 2022-09-28T07:40:04+00:00 | {"annotations_creators": ["expert-generated", "crowdsourced", "machine-generated"], "language_creators": ["crowdsourced", "expert-generated"], "language": ["en"], "license": ["cc-by-4.0", "apache-2.0", "cc0-1.0", "cc-by-nc-3.0", "other"], "multilinguality": ["monolingual"], "size_categories": ["100K<n<1M", "1M<n<10M"],... | 2022-10-14T13:30:30+00:00 | [] | [
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All eight of datasets in ESC can be downloaded and prepared in just a single line of code through the Hugging Face Datasets library:
- '"esc-benchmark"': the repository namespace. This is fixed for all ESC datasets.
- '"librispeech"': the dataset name. This can be changed to any of any one of the eight datasets in... | [
"## Dataset Information\n\nA data point can be accessed by indexing the dataset object loaded through 'load_dataset':\n\n\n\nA typical data point comprises the path to the audio file and its transcription. Also included is information of the dataset from which the sample derives and a unique identifier name:",
"#... | [
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70ae446852c18cf146a29082a2acf66e74609cd8 | # dureader
数据来自DuReader-Retreval数据集，这里是[原始地址](https://github.com/baidu/DuReader/tree/master/DuReader-Retrieval)。
> 本数据集只用作学术研究使用。如果本仓库涉及侵权行为，会立即删除。 | zyznull/dureader-retrieval-ranking | [
"license:apache-2.0",
"region:us"
] | 2022-09-28T08:00:20+00:00 | {"license": "apache-2.0"} | 2023-01-03T08:05:57+00:00 | [] | [] | TAGS
#license-apache-2.0 #region-us
| # dureader
数据来自DuReader-Retreval数据集，这里是原始地址。
> 本数据集只用作学术研究使用。如果本仓库涉及侵权行为，会立即删除。 | [
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] |
0d792180b9349c544a2ea220de6b72f78611fb17 | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Summarization
* Model: facebook/bart-large-cnn
* Dataset: big_patent
* Config: g
* Split: validation
To run new evaluation jobs, vis... | autoevaluate/autoeval-eval-big_patent-g-9d42aa-1581555947 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-09-28T08:54:38+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["big_patent"], "eval_info": {"task": "summarization", "model": "facebook/bart-large-cnn", "metrics": ["perplexity"], "dataset_name": "big_patent", "dataset_config": "g", "dataset_split": "validation", "col_mapping": {"text": "description", "targe... | 2022-09-28T10:15:24+00:00 | [] | [] | TAGS
#autotrain #evaluation #region-us
| # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Summarization
* Model: facebook/bart-large-cnn
* Dataset: big_patent
* Config: g
* Split: validation
To run new evaluation jobs, visit Hugging Face's automatic model ev... | [
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Summarization\n* Model: facebook/bart-large-cnn\n* Dataset: big_patent\n* Config: g\n* Split: validation\n\nTo run new evaluation jobs, visit Hugging Face's aut... | [
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c801dc186b40a532c5820b4662570390da90431b | # Dataset Card for "tacred"
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)... | DFKI-SLT/tacred | [
"task_categories:text-classification",
"task_ids:multi-class-classification",
"annotations_creators:crowdsourced",
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"language_creators:found",
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"size_categories:100K<n<1M",
"source_datasets:extended|other",
"language:en",
"licen... | 2022-09-28T09:02:34+00:00 | {"annotations_creators": ["crowdsourced", "expert-generated"], "language_creators": ["found"], "language": ["en"], "license": ["other"], "multilinguality": ["monolingual"], "size_categories": ["100K<n<1M"], "source_datasets": ["extended|other"], "task_categories": ["text-classification"], "task_ids": ["multi-class-clas... | 2023-05-17T11:55:00+00:00 | [
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=========================
Table of Contents
-----------------
* Table of Contents
* Dataset Description
+ Dataset Summary
+ Supported Tasks and Leaderboards
+ Languages
* Dataset Structure
+ Data Instances
+ Data Fields
+ Data Splits
* Dataset Creation
+ Curation Rationale
+ Source... | [
"### Dataset Summary\n\n\nThe TAC Relation Extraction Dataset (TACRED) is a large-scale relation extraction dataset with 106,264 examples built over newswire and web text from the corpus used in the yearly TAC Knowledge Base Population (TAC KBP) challenges. Examples in TACRED cover 41 relation types as used in the ... | [
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c385a6a9a7c200cde48d6b7ed171e9187db8c99a | ---
annotations_creators:
- found
language_creators:
- found
language:
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license:
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multilinguality:
- monolingual
pretty_name: disTD
task_categories:
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task_ids:
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dataset_info:
features:
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sequence: string
- name: isDisf
sequence:
... | EmnaBou/tokenDS | [
"region:us"
] | 2022-09-28T10:34:05+00:00 | {} | 2022-11-30T11:32:39+00:00 | [] | [] | TAGS
#region-us
| ---
annotations_creators:
- found
language_creators:
- found
language:
- ar
license:
- other
multilinguality:
- monolingual
pretty_name: disTD
task_categories:
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task_ids:
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dataset_info:
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sequence: string
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91e996a3d990bddbd4c554f54ebe821afc978fb9 |
# UD_Catalan-AnCora
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- ... | projecte-aina/UD_Catalan-AnCora | [
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"license:cc-by-4.0",
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] | 2022-09-28T10:51:06+00:00 | {"annotations_creators": ["expert-generated"], "language_creators": ["found"], "language": ["ca"], "license": ["cc-by-4.0"], "multilinguality": ["monolingual"], "size_categories": [], "source_datasets": [], "task_categories": ["token-classification"], "task_ids": ["part-of-speech"], "pretty_name": "UD_Catalan-AnCora", ... | 2023-11-25T06:31:40+00:00 | [] | [
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|
# UD_Catalan-AnCora
## Table of Contents
- Table of Contents
- Dataset Description
- Dataset Summary
- Supported Tasks and Leaderboards
- Languages
- Dataset Structure
- Data Instances
- Data Fields
- Data Splits
- Dataset Creation
- Curation Rationale
- Source Data
- Annotations
- Personal and S... | [
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8a5e23f6ffbd1b55efaf0ffe6322f985fe859bf2 |
# Dataset Card for xP3
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
... | bigscience/xP3mt | [
"task_categories:other",
"annotations_creators:expert-generated",
"annotations_creators:crowdsourced",
"multilinguality:multilingual",
"size_categories:100M<n<1B",
"language:ak",
"language:ar",
"language:as",
"language:bm",
"language:bn",
"language:ca",
"language:code",
"language:en",
"lan... | 2022-09-28T11:36:00+00:00 | {"annotations_creators": ["expert-generated", "crowdsourced"], "language": ["ak", "ar", "as", "bm", "bn", "ca", "code", "en", "es", "eu", "fon", "fr", "gu", "hi", "id", "ig", "ki", "kn", "lg", "ln", "ml", "mr", "ne", "nso", "ny", "or", "pa", "pt", "rn", "rw", "sn", "st", "sw", "ta", "te", "tn", "ts", "tum", "tw", "ur",... | 2023-05-30T14:50:57+00:00 | [
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... | TAGS
#task_categories-other #annotations_creators-expert-generated #annotations_creators-crowdsourced #multilinguality-multilingual #size_categories-100M<n<1B #language-Akan #language-Arabic #language-Assamese #language-Bambara #language-Bengali #language-Catalan #language-code #language-English #language-Spanish #lang... | Dataset Card for xP3
====================
Table of Contents
-----------------
* Table of Contents
* Dataset Description
+ Dataset Summary
+ Supported Tasks and Leaderboards
+ Languages
* Dataset Structure
+ Data Instances
+ Data Fields
+ Data Splits
* Dataset Creation
+ Curation Rationale
+ Source Data
+ A... | [
"### Dataset Summary\n\n\n\n> \n> xP3 (Crosslingual Public Pool of Prompts) is a collection of prompts & datasets across 46 of languages & 16 NLP tasks. It is used for the training of BLOOMZ and mT0, multilingual language models capable of following human instructions in dozens of languages zero-shot.\n> \n> \n> \n... | [
"TAGS\n#task_categories-other #annotations_creators-expert-generated #annotations_creators-crowdsourced #multilinguality-multilingual #size_categories-100M<n<1B #language-Akan #language-Arabic #language-Assamese #language-Bambara #language-Bengali #language-Catalan #language-code #language-English #language-Spanish... | [
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cc06d31cd266a978219b212ba00e72eb0ad14d4c | a | CANUTO/images | [
"region:us"
] | 2022-09-28T14:54:45+00:00 | {} | 2022-09-28T15:00:43+00:00 | [] | [] | TAGS
#region-us
| a | [] | [
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e91596d78fb16f41a5b993e2db7d4345bca01d77 | #Training IA Model
Here are the images that i used to train an a SD model with "tiomonkey" concept | EltioMonkey/MonkeyTrain | [
"region:us"
] | 2022-09-28T17:52:43+00:00 | {} | 2022-09-29T16:44:43+00:00 | [] | [] | TAGS
#region-us
| #Training IA Model
Here are the images that i used to train an a SD model with "tiomonkey" concept | [] | [
"TAGS\n#region-us \n"
] | [
6
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d23b094346c5dbda1080a74bb2a24c18adbf7409 |
# Dataset Card for MultiPL-E
## Dataset Description
- **Homepage:** https://nuprl.github.io/MultiPL-E/
- **Repository:** https://github.com/nuprl/MultiPL-E
- **Paper:** https://ieeexplore.ieee.org/abstract/document/10103177
- **Point of Contact:** carolyn.anderson@wellesley.edu, mfeldman@oberlin.edu, a.guha@northe... | nuprl/MultiPL-E | [
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"language_creators:machine-generated",
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"size_categories:1K<n<10K",
"source_datasets:original",
"source_datasets:extended|openai_humaneval",
"source_datasets:extended|mbpp",
"language:en",
... | 2022-09-28T18:20:07+00:00 | {"annotations_creators": ["machine-generated"], "language_creators": ["machine-generated", "expert-generated"], "language": ["en"], "license": ["mit"], "multilinguality": ["monolingual"], "size_categories": ["1K<n<10K"], "source_datasets": ["original", "extended|openai_humaneval", "extended|mbpp"], "task_categories": [... | 2023-06-15T23:08:57+00:00 | [] | [
"en"
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|
# Dataset Card for MultiPL-E
## Dataset Description
- Homepage: URL
- Repository: URL
- Paper: URL
- Point of Contact: carolyn.anderson@URL, mfeldman@URL, a.guha@URL
## Dataset Summary
MultiPL-E is a dataset for evaluating large language models for code
generation that supports 18 programming languages. It takes... | [
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"## Dataset Summary\n\nMultiPL-E is a dataset for evaluating large language models for code\ngeneration that supports 18 programming... | [
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5c9e80ea311d9ab56264265b77ed06a1d32bcef0 |
# Cannabis Licenses
<!-- FIXME:
<div align="center" style="text-align:center; margin-top:1rem; margin-bottom: 1rem;">
<img style="max-height:365px;width:100%;max-width:720px;" alt="" src="analysis/figures/cannabis-licenses-map.png">
</div> -->
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Datas... | cannlytics/cannabis_licenses | [
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"license:cc-by-4.0",
"cannabis",
"licenses",
"region:us"
] | 2022-09-28T18:52:23+00:00 | {"annotations_creators": ["expert-generated"], "language_creators": ["expert-generated"], "license": ["cc-by-4.0"], "pretty_name": "cannabis_licenses", "tags": ["cannabis", "licenses"]} | 2023-09-30T13:23:05+00:00 | [] | [] | TAGS
#annotations_creators-expert-generated #language_creators-expert-generated #license-cc-by-4.0 #cannabis #licenses #region-us
| Cannabis Licenses
=================
Table of Contents
-----------------
* Table of Contents
* Dataset Description
+ Dataset Summary
* Dataset Structure
+ Data Instances
+ Data Fields
+ Data Splits
* Dataset Creation
+ Curation Rationale
+ Source Data
+ Data Collection and Normalization
+ Personal and Sensit... | [
"### Dataset Summary\n\n\nCannabis Licenses is a collection of cannabis license data for each state with permitted adult-use cannabis. The dataset also includes a sub-dataset, 'all', that includes all licenses.\n\n\nDataset Structure\n-----------------\n\n\nThe dataset is partitioned into 18 subsets for each state ... | [
"TAGS\n#annotations_creators-expert-generated #language_creators-expert-generated #license-cc-by-4.0 #cannabis #licenses #region-us \n",
"### Dataset Summary\n\n\nCannabis Licenses is a collection of cannabis license data for each state with permitted adult-use cannabis. The dataset also includes a sub-dataset, '... | [
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3562204543b81d961ccef05e11e3d69011fe5104 | # ****Dataset Card for tathagata****
# **I-Dataset Summary**
tathagata.txt is a dataset based on summaries of major Buddhist, Hindu and Advaita texts such as:
- Diamond Sutra
- Lankavatara Sutra
- Sri Nisargadatta Maharaj quotes
- Quotes from the Bhagavad Gita
This dataset was used to train this model https://huggingf... | radm/tathagata | [
"task_categories:text-generation",
"task_ids:language-modeling",
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"language:ru",
"license:apache-2.0",
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"region:us"
] | 2022-09-28T18:55:18+00:00 | {"annotations_creators": ["found"], "language_creators": ["found"], "language": ["ru"], "license": ["apache-2.0"], "multilinguality": ["monolingual"], "size_categories": ["n<1K"], "source_datasets": ["original"], "task_categories": ["text-generation"], "task_ids": ["language-modeling"], "pretty_name": "tathagata", "tag... | 2022-09-28T19:20:13+00:00 | [] | [
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| # Dataset Card for tathagata
# I-Dataset Summary
URL is a dataset based on summaries of major Buddhist, Hindu and Advaita texts such as:
- Diamond Sutra
- Lankavatara Sutra
- Sri Nisargadatta Maharaj quotes
- Quotes from the Bhagavad Gita
This dataset was used to train this model URL
# II-Languages
The texts in the d... | [
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"# II-Languag... | [
"TAGS\n#task_categories-text-generation #task_ids-language-modeling #annotations_creators-found #language_creators-found #multilinguality-monolingual #size_categories-n<1K #source_datasets-original #language-Russian #license-apache-2.0 #text_generation #quotes #region-us \n",
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1786207ffebfbe62211179fccbd4d0566ace37a9 | This textual inversion has been trained on WaifuDiffusion v1.2 (`[45dee52b]`). This will probably not work well with the standard Stable Diffusion model.
# How to use (with webui)
- create `embeddings` folder in the root directory of the webui
- paste the .bin in there
**keyword: `<marine>`** | cattoroboto/waifudiffusion-marine-textual-inversion | [
"region:us"
] | 2022-09-28T22:30:57+00:00 | {} | 2022-09-28T23:06:45+00:00 | [] | [] | TAGS
#region-us
| This textual inversion has been trained on WaifuDiffusion v1.2 ('[45dee52b]'). This will probably not work well with the standard Stable Diffusion model.
# How to use (with webui)
- create 'embeddings' folder in the root directory of the webui
- paste the .bin in there
keyword: '<marine>' | [
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337ec38c58a30812c0944d807f5acdc1f86f4bc3 | # Info
> This is a repository for anime regularization. If you wish to contribute to the dataset, contact me at naotsue#9786. I will add them to the dataset and update it.
# Criteria
> 512x512
> No excessive deformations
> Vaguely resembles an anime artstyle
# Contribution Leaderboard
> 1. bWm_nubby: 5838 images
>... | waifu-research-department/regularization | [
"license:mit",
"region:us"
] | 2022-09-29T01:09:44+00:00 | {"license": "mit"} | 2022-09-29T21:00:10+00:00 | [] | [] | TAGS
#license-mit #region-us
| # Info
> This is a repository for anime regularization. If you wish to contribute to the dataset, contact me at naotsue#9786. I will add them to the dataset and update it.
# Criteria
> 512x512
> No excessive deformations
> Vaguely resembles an anime artstyle
# Contribution Leaderboard
> 1. bWm_nubby: 5838 images
>... | [
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4d7946ef7f0c5ff5e261e384db8015dfe8e417cb |
# Dataset Card for EurlexResources: A Corpus Covering the Largest EURLEX Resources
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [... | joelniklaus/eurlex_resources | [
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"language:e... | 2022-09-29T06:35:34+00:00 | {"annotations_creators": ["other"], "language_creators": ["found"], "language": ["bg", "cs", "da", "de", "el", "en", "es", "et", "fi", "fr", "ga", "hr", "hu", "it", "lt", "lv", "mt", "nl", "pl", "pt", "ro", "sk", "sl", "sv"], "license": ["cc-by-4.0"], "multilinguality": ["multilingual"], "size_categories": ["1M<n<10M"]... | 2023-05-10T07:04:28+00:00 | [] | [
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================================================================================
Table of Contents
-----------------
* Table of Contents
* Dataset Description
+ Dataset Summary
+ Supported Tasks and Leaderboards
+ Languages
* Datase... | [
"### Dataset Summary\n\n\nThis dataset contains large text resources (~179GB in total) from EURLEX that can be used for pretraining language models.\n\n\nUse the dataset like this:",
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"### Languages\n\n\nThe f... | [
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e5f041fc5d507821b395ff746d57f97818bd8db1 |
# Dataset Card for Weakly supervised AG News Dataset
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Stru... | bergr7/weakly_supervised_ag_news | [
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"multilinguality:monolingual",
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"region:us"
] | 2022-09-29T07:43:34+00:00 | {"annotations_creators": [], "language_creators": ["other"], "language": ["en"], "license": [], "multilinguality": ["monolingual"], "size_categories": ["1K<n<10K"], "source_datasets": ["extended|ag_news"], "task_categories": ["text-classification"], "task_ids": ["multi-class-classification"], "pretty_name": "Weakly sup... | 2022-10-06T11:51:52+00:00 | [] | [
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|
# Dataset Card for Weakly supervised AG News Dataset
## Table of Contents
- Table of Contents
- Dataset Description
- Dataset Summary
- Supported Tasks and Leaderboards
- Languages
- Dataset Structure
- Data Instances
- Data Fields
- Data Splits
- Dataset Creation
- Curation Rationale
- Source Data
-... | [
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f6323032886e971c842c7b0b5b9f3592e6e2bd0a | Ces images de nuages sont divisées en 2 classes, les cirrus et les cumulus.
These cloud images are divided into 2 classes, cirrus and cumulus. | Doudou69/Cloud_Recognition | [
"region:us"
] | 2022-09-29T08:48:44+00:00 | {} | 2022-09-29T09:19:04+00:00 | [] | [] | TAGS
#region-us
| Ces images de nuages sont divisées en 2 classes, les cirrus et les cumulus.
These cloud images are divided into 2 classes, cirrus and cumulus. | [] | [
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] | [
6
] | [
"passage: TAGS\n#region-us \n"
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81b731b90a2a11229c78e6791d0d8c1ccf6833d4 | # Dataset Card for [Dataset Name]
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-stru... | merkalo-ziri/vsosh2022 | [
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"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"language:ru",
"license:other",
"region:us"
] | 2022-09-29T09:35:38+00:00 | {"annotations_creators": ["found"], "language_creators": ["found"], "language": ["ru"], "license": ["other"], "multilinguality": ["monolingual"], "size_categories": ["1K<n<10K"], "source_datasets": [], "task_categories": ["text-classification"], "task_ids": ["sentiment-classification"], "pretty_name": "vsosh_dataset", ... | 2022-09-29T10:02:34+00:00 | [] | [
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| # Dataset Card for [Dataset Name]
## Table of Contents
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e214dad7ae9dd678a2f01c9220d45d42c94c8f91 |
# Dataset Card for MC4_Legal: A Corpus Covering the Legal Part of MC4 for European Languages
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboard... | joelniklaus/mc4_legal | [
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===========================================================================================
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# Dataset Card for AISegment.cn - Matting Human datasets
## Table of Contents
- [Dataset Card for AISegment.cn - Matting Human datasets](#dataset-card-for-aisegmentcn---matting-human-datasets)
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
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# Dataset Card for URL - Matting Human datasets
## Table of Contents
- Dataset Card for URL - Matting Human datasets
- Table of Contents
- Dataset Description
- Dataset Structure
- Licensing Information
## Dataset Description
Quoting the dataset's github (translated by Apple Translator):
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d921ec7e349ce0d28daf30b2da9da5ee698bef0d |
# Dataset Card for MIRACL Corpus
## Dataset Description
* **Homepage:** http://miracl.ai
* **Repository:** https://github.com/project-miracl/miracl
* **Paper:** https://arxiv.org/abs/2210.09984
MIRACL 🌍🙌🌏 (Multilingual Information Retrieval Across a Continuum of Languages) is a multilingual retrieval dataset tha... | miracl/miracl-corpus | [
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==============================
Dataset Description
-------------------
* Homepage: URL
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aa4f6645451098df234769f89af1fcccd16d567f | ---
license: othera
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f0f37162e31f17be4a703fc555be1a965b77adf5 | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-66b
* Dataset: mathemakitten/winobias_antistereotype_test
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#autotrain #evaluation #region-us
| # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
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4ab783c3e7e2cc5ca9ea75ab922b856f096e6b9e | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
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8881f6b4ef7d33351a0e5b73d482b280bf35992e | # Dataset Card for AutoTrain Evaluator
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4f0ea713c9fbb0e90fb46605a9d6fa40045c0cb7 | # Dataset Card for AutoTrain Evaluator
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26eec3ffb27c97bfd5b123dae4f046a6c6cb2676 | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
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4cf687b19fb10893ab4f13a9e2bec3323150897b | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
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"passage: TAGS\n#autotrain #evaluation #region-us \n# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Zero-Shot Text Classification\n* Model: facebook/opt-350m\n* Dataset: mathemakitten/winobias_antistereotype_t... |
40811b7d45e7be647accbaad064231273e3d5ff0 | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-30b
* Dataset: mathemakitten/winobias_antistereotype_test
* Config: mathemakitten... | autoevaluate/autoeval-eval-mathemakitten__winobias_antistereotype_test-mathemakitt-c50da3-1597456335 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-09-29T14:31:29+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["mathemakitten/winobias_antistereotype_test"], "eval_info": {"task": "text_zero_shot_classification", "model": "facebook/opt-30b", "metrics": [], "dataset_name": "mathemakitten/winobias_antistereotype_test", "dataset_config": "mathemakitten--wino... | 2022-09-29T15:38:50+00:00 | [] | [] | TAGS
#autotrain #evaluation #region-us
| # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-30b
* Dataset: mathemakitten/winobias_antistereotype_test
* Config: mathemakitten--winobias_antistereotype_test
* Spl... | [
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1201e7301176c674f1f05bd1d01787c919b1ea76 | # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-13b
* Dataset: mathemakitten/winobias_antistereotype_test
* Config: mathemakitten... | autoevaluate/autoeval-eval-mathemakitten__winobias_antistereotype_test-mathemakitt-c50da3-1597456334 | [
"autotrain",
"evaluation",
"region:us"
] | 2022-09-29T14:31:36+00:00 | {"type": "predictions", "tags": ["autotrain", "evaluation"], "datasets": ["mathemakitten/winobias_antistereotype_test"], "eval_info": {"task": "text_zero_shot_classification", "model": "facebook/opt-13b", "metrics": [], "dataset_name": "mathemakitten/winobias_antistereotype_test", "dataset_config": "mathemakitten--wino... | 2022-09-29T14:59:04+00:00 | [] | [] | TAGS
#autotrain #evaluation #region-us
| # Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by AutoTrain for the following task and dataset:
* Task: Zero-Shot Text Classification
* Model: facebook/opt-13b
* Dataset: mathemakitten/winobias_antistereotype_test
* Config: mathemakitten--winobias_antistereotype_test
* Spl... | [
"# Dataset Card for AutoTrain Evaluator\n\nThis repository contains model predictions generated by AutoTrain for the following task and dataset:\n\n* Task: Zero-Shot Text Classification\n* Model: facebook/opt-13b\n* Dataset: mathemakitten/winobias_antistereotype_test\n* Config: mathemakitten--winobias_antistereotyp... | [
"TAGS\n#autotrain #evaluation #region-us \n",
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9704434c1038783fb4eb69ffc76b029e2ea43643 | annotations_creators:
- no-annotation
language:
- en
language_creators:
- other
license:
- artistic-2.0
multilinguality:
- monolingual
pretty_name: m3 dataset (a dataset with my face in it)
size_categories:
- n<1K
source_datasets:
- original
tags: []
task_categories:
- text-to-image
task_ids: [] | Gr3en/m3 | [
"region:us"
] | 2022-09-29T15:07:05+00:00 | {} | 2022-09-29T16:13:42+00:00 | [] | [] | TAGS
#region-us
| annotations_creators:
- no-annotation
language:
- en
language_creators:
- other
license:
- artistic-2.0
multilinguality:
- monolingual
pretty_name: m3 dataset (a dataset with my face in it)
size_categories:
- n<1K
source_datasets:
- original
tags: []
task_categories:
- text-to-image
task_ids: [] | [] | [
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] | [
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"region:us"
] | 2022-09-29T16:08:56+00:00 | {} | 2022-09-29T16:12:35+00:00 | [] | [] | TAGS
#region-us
| yes | [] | [
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d81cbab7d0392708d5371d3a4960e69261824db4 |
# Dataset Card for New Yorker Caption Contest Benchmarks
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset... | jmhessel/newyorker_caption_contest | [
"task_categories:image-to-text",
"task_categories:multiple-choice",
"task_categories:text-classification",
"task_categories:text-generation",
"task_categories:visual-question-answering",
"task_categories:other",
"task_categories:text2text-generation",
"task_ids:multi-class-classification",
"task_ids... | 2022-09-29T16:28:05+00:00 | {"annotations_creators": ["expert-generated", "crowdsourced", "found"], "language_creators": ["crowdsourced", "expert-generated"], "language": ["en"], "license": ["cc-by-4.0"], "multilinguality": ["monolingual"], "size_categories": ["1K<n<10K"], "source_datasets": ["original"], "task_categories": ["image-to-text", "mul... | 2023-12-22T19:13:58+00:00 | [
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# Dataset Card for New Yorker Caption Contest Benchmarks
## Table of Contents
- Table of Contents
- Dataset Description
- Dataset Summary
- Supported Tasks and Leaderboards
- Languages
- Dataset Structure
- Data Instances
- Data Fields
- Data Splits
- Dataset Creation
- Curation Rationale
- Source Dat... | [
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d2e593d645e8b7d71ab76738be13269f96b0139b | # AutoTrain Dataset for project: github-emotion-surprise
## Dataset Description
Dataset used in the paper: Imran et al., ["Data Augmentation for Improving Emotion Recognition in Software Engineering Communication"](https://arxiv.org/abs/2208.05573), ASE-2022.
### Languages
The BCP-47 code for the dataset's language... | imranraad/github-emotion-surprise | [
"task_categories:text-classification",
"arxiv:2208.05573",
"doi:10.57967/hf/0050",
"region:us"
] | 2022-09-29T20:03:25+00:00 | {"task_categories": ["text-classification"]} | 2022-10-20T09:18:22+00:00 | [
"2208.05573"
] | [] | TAGS
#task_categories-text-classification #arxiv-2208.05573 #doi-10.57967/hf/0050 #region-us
| AutoTrain Dataset for project: github-emotion-surprise
======================================================
Dataset Description
-------------------
Dataset used in the paper: Imran et al., "Data Augmentation for Improving Emotion Recognition in Software Engineering Communication", ASE-2022.
### Languages
The ... | [
"### Languages\n\n\nThe BCP-47 code for the dataset's language is unk.\n\n\nDataset Structure\n-----------------",
"### Data Instances\n\n\nA sample from this dataset looks as follows:",
"### Dataset Fields\n\n\nThe dataset has the following fields (also called \"features\"):",
"### Dataset Splits\n\n\nThis d... | [
"TAGS\n#task_categories-text-classification #arxiv-2208.05573 #doi-10.57967/hf/0050 #region-us \n",
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"### Data Instances\n\n\nA sample from this dataset looks as follows:",
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8d818753c4d4b3541433a20d2a7008e4e3cfa427 | pictures | wallyg/Pictures | [
"region:us"
] | 2022-09-29T20:04:21+00:00 | {} | 2022-09-29T20:20:59+00:00 | [] | [] | TAGS
#region-us
| pictures | [] | [
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3d4df382ad4507ff652d99e244bb3e3c1532d0a0 | # AutoTrain Dataset for project: github-emotion-love
## Dataset Description
Dataset used in the paper: Imran et al., ["Data Augmentation for Improving Emotion Recognition in Software Engineering Communication"](https://arxiv.org/abs/2208.05573), ASE-2022.
### Languages
The BCP-47 code for the dataset's language is ... | imranraad/github-emotion-love | [
"task_categories:text-classification",
"arxiv:2208.05573",
"doi:10.57967/hf/0049",
"region:us"
] | 2022-09-29T20:10:30+00:00 | {"task_categories": ["text-classification"]} | 2022-10-20T09:18:07+00:00 | [
"2208.05573"
] | [] | TAGS
#task_categories-text-classification #arxiv-2208.05573 #doi-10.57967/hf/0049 #region-us
| AutoTrain Dataset for project: github-emotion-love
==================================================
Dataset Description
-------------------
Dataset used in the paper: Imran et al., "Data Augmentation for Improving Emotion Recognition in Software Engineering Communication", ASE-2022.
### Languages
The BCP-47 c... | [
"### Languages\n\n\nThe BCP-47 code for the dataset's language is unk.\n\n\nDataset Structure\n-----------------",
"### Data Instances\n\n\nA sample from this dataset looks as follows:",
"### Dataset Fields\n\n\nThe dataset has the following fields (also called \"features\"):",
"### Dataset Splits\n\n\nThis d... | [
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"### Languages\n\n\nThe BCP-47 code for the dataset's language is unk.\n\n\nDataset Structure\n-----------------",
"### Data Instances\n\n\nA sample from this dataset looks as follows:",
"### Dataset Fields\n\n... | [
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6a151c5d80f3c0d00af267e030daca4f42df9012 | Imagenes:
"https://huggingface.co/datasets/sati93/fotos/resolve/main/me1.jpg",
"https://huggingface.co/datasets/sati93/fotos/resolve/main/me2.jpg",
"https://huggingface.co/datasets/sati93/fotos/resolve/main/me3.jpg",
"https://huggingface.co/datasets/sati93/fotos/resolve/main/me4.jpg",
"htt... | sati93/fotos | [
"region:us"
] | 2022-09-29T23:28:59+00:00 | {} | 2022-10-02T19:19:26+00:00 | [] | [] | TAGS
#region-us
| Imagenes:
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Configuracion:
instance_prompt: sati
prior_preservation_... | [] | [
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] | [
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627e5cc137bcd577a9769bbb108ff97c65cd8aac | scratch directory for storing image datasets which are processed through a clip embedding model!
---
license: mit
---
| murphyk/dogs-cats-small-clip-embedding | [
"region:us"
] | 2022-09-30T00:38:19+00:00 | {} | 2022-09-30T02:46:33+00:00 | [] | [] | TAGS
#region-us
| scratch directory for storing image datasets which are processed through a clip embedding model!
---
license: mit
---
| [] | [
"TAGS\n#region-us \n"
] | [
6
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"passage: TAGS\n#region-us \n"
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e99e27c90f20307ebbefd7e79e35255a62de3118 |
# Dataset Card for Reflections in Peer Counseling
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Struct... | emoneil/reflections-in-peer-counseling | [
"task_categories:summarization",
"task_categories:text-generation",
"task_categories:conversational",
"task_ids:dialogue-generation",
"annotations_creators:expert-generated",
"size_categories:1K<n<10K",
"gpt3",
"natural language processing",
"natural language generation",
"peer counseling",
"reg... | 2022-09-30T03:21:28+00:00 | {"annotations_creators": ["expert-generated"], "language_creators": [], "language": [], "license": [], "size_categories": ["1K<n<10K"], "source_datasets": [], "task_categories": ["summarization", "text-generation", "conversational"], "task_ids": ["dialogue-generation"], "pretty_name": "Reflections in Peer Counseling", ... | 2022-10-14T02:59:04+00:00 | [] | [] | TAGS
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|
# Dataset Card for Reflections in Peer Counseling
## Table of Contents
- Table of Contents
- Dataset Description
- Dataset Summary
- Supported Tasks and Leaderboards
- Languages
- Dataset Structure
- Data Instances
- Data Fields
- Data Splits
- Dataset Creation
- Curation Rationale
- Source Data
- A... | [
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6685505e1e3c02ac0483398e633922b31de89fb0 |
## Dataset Description
A segmentation dataset for anime character
My project: [anime-segmentation](https://github.com/SkyTNT/anime-segmentation)
### Dataset Summary
| Dir | Description | Format | Images |
| ---- | ---- | ---- | ---- |
| bg |... | skytnt/anime-segmentation | [
"task_categories:image-segmentation",
"task_ids:semantic-segmentation",
"size_categories:10K<n<100K",
"source_datasets:original",
"license:cc0-1.0",
"region:us"
] | 2022-09-30T04:27:06+00:00 | {"annotations_creators": [], "language_creators": [], "language": [], "license": ["cc0-1.0"], "multilinguality": [], "size_categories": ["10K<n<100K"], "source_datasets": ["original"], "task_categories": ["image-segmentation"], "task_ids": ["semantic-segmentation"], "pretty_name": "Anime Segmentation", "tags": []} | 2022-10-03T00:35:40+00:00 | [] | [] | TAGS
#task_categories-image-segmentation #task_ids-semantic-segmentation #size_categories-10K<n<100K #source_datasets-original #license-cc0-1.0 #region-us
| Dataset Description
-------------------
A segmentation dataset for anime character
My project: anime-segmentation
### Dataset Summary
Total size: 18GB
### Collection Method
Collect background from character\_bg\_seg\_data
Collect foreground from danbooru website.
Collect imgs and masks from AniSeg and ... | [
"### Dataset Summary\n\n\n\nTotal size: 18GB",
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2fc722a09b37bee7ea8bbf850f59f004c7bb5c15 |
All eight of datasets in ESC can be downloaded and prepared in just a single line of code through the Hugging Face Datasets library:
```python
from datasets import load_dataset
librispeech = load_dataset("esc-benchmark/esc-datasets", "librispeech", split="train")
```
- `"esc-benchmark"`: the repository namespace. T... | esc-bench/esc-datasets | [
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"annotations_creators:crowdsourced",
"annotations_creators:machine-generated",
"language_creators:crowdsourced",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
... | 2022-09-30T07:32:42+00:00 | {"annotations_creators": ["expert-generated", "crowdsourced", "machine-generated"], "language_creators": ["crowdsourced", "expert-generated"], "language": ["en"], "license": ["cc-by-4.0", "apache-2.0", "cc0-1.0", "cc-by-nc-3.0", "other"], "multilinguality": ["monolingual"], "size_categories": ["100K<n<1M", "1M<n<10M"],... | 2022-10-21T13:34:49+00:00 | [] | [
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] | TAGS
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All eight of datasets in ESC can be downloaded and prepared in just a single line of code through the Hugging Face Datasets library:
- '"esc-benchmark"': the repository namespace. This is fixed for all ESC datasets.
- '"librispeech"': the dataset name. This can be changed to any of any one of the eight datasets in... | [
"## Dataset Information\n\nA data point can be accessed by indexing the dataset object loaded through 'load_dataset':\n\n\n\nA typical data point comprises the path to the audio file and its transcription. Also included is information of the dataset from which the sample derives and a unique identifier name:",
"#... | [
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73cb1384b467451a0c32c1851b712a7e90a9bc57 |
# Dataset Card for PP4AV
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [D... | khaclinh/testdata | [
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|
# Dataset Card for PP4AV
## Table of Contents
- Table of Contents
- Dataset Description
- Dataset Summary
- Languages
- Dataset Structure
- Data Instances
- Data Fields
- Dataset Creation
- Source Data
- Annotations
- Personal and Sensitive Information
- Considerations for Using the Data
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56584831fefeb7d6cef37df192c05f4ad8b8fc00 | This dataset contains images for the classification of bees and ants | delima87/beesvsants | [
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] | 2022-09-30T08:26:04+00:00 | {} | 2022-09-30T08:34:41+00:00 | [] | [] | TAGS
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3191d1da8882b20445722fe811b70533412e2173 | # Dataset Card for "MultiTACRED"
## Dataset Description
- **Homepage:** [https://github.com/DFKI-NLP/MultiTACRED](https://github.com/DFKI-NLP/MultiTACRED)
- **Paper:** [MultiTACRED: A Multilingual Version of the TAC Relation Extraction Dataset](https://arxiv.org/abs/2305.04582)
- **Point of Contact:** See [https://git... | DFKI-SLT/multitacred | [
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"language:ar",
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"lan... | 2022-09-30T10:31:31+00:00 | {"annotations_creators": ["crowdsourced", "expert-generated"], "language_creators": ["found"], "language": ["ar", "de", "es", "fi", "fr", "hi", "hu", "ja", "pl", "ru", "tr", "zh"], "license": "other", "size_categories": ["100K<n<1M"], "source_datasets": ["DFKI-NLP/tacred"], "task_categories": ["text-classification"], "... | 2024-01-17T09:16:51+00:00 | [
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==============================
Dataset Description
-------------------
* Homepage: URL
* Paper: MultiTACRED: A Multilingual Version of the TAC Relation Extraction Dataset
* Point of Contact: See URL
* Size of downloaded dataset files: 15.4KB (TACRED-Revisited), 3.7 MB (Re-TACRED)
* Si... | [
"### Dataset Summary\n\n\nMultiTACRED is a multilingual version of the large-scale TAC Relation Extraction Dataset.\nIt covers 12 typologically diverse languages from 9 language families, and was created by the\nSpeech & Language Technology group of DFKI by machine-translating the instances of the\noriginal TACRED ... | [
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ca9324836eefa4c1d7bc835afcaace6759dc3202 | The data contains three different vehicles from CCSA (https://www.ccsa.gmu.edu/models/):
A Toyota Yaris
A Chevy Silverado
And an ADS vehicle
These vehicles were tested at different speeds, and the binout files were stored.
The car models were used to develop an AI that could estimate a full frontal impact... | holen/Finite_element_crash_data | [
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"region:us"
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#license-apache-2.0 #region-us
| The data contains three different vehicles from CCSA (URL
A Toyota Yaris
A Chevy Silverado
And an ADS vehicle
These vehicles were tested at different speeds, and the binout files were stored.
The car models were used to develop an AI that could estimate a full frontal impact for different cars at differen... | [] | [
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3b04f22b6b00133646c814aac26785a428acdaad |
This is the Faroese Common Crawl corpus. The largest dataset of mono-lingual Faroese text, it was extracted from the Common Crawl.
If you find this dataset useful, please cite
```
@inproceedings{snaebjarnarson-etal-2023-transfer,
title = "{T}ransfer to a Low-Resource Language via Close Relatives: The Case Study ... | vesteinn/FC3 | [
"language:fo",
"license:cc",
"region:us"
] | 2022-09-30T11:09:39+00:00 | {"language": ["fo"], "license": "cc", "pretty_name": "FC3"} | 2023-03-23T15:51:34+00:00 | [] | [
"fo"
] | TAGS
#language-Faroese #license-cc #region-us
|
This is the Faroese Common Crawl corpus. The largest dataset of mono-lingual Faroese text, it was extracted from the Common Crawl.
If you find this dataset useful, please cite
| [] | [
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22ed42ff72e12eac2938306f120987e9b3e4c711 |
# Dataset Card for SMG-NFT
## Examples
## Citation
| pking/SMG-NFT | [
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] | 2022-09-30T11:20:49+00:00 | {"annotations_creators": ["machine-generated"], "language_creators": ["other"], "language": ["en"], "license": "cc-by-nc-sa-4.0", "multilinguality": ["monolingual"], "size_categories": ["n<1K"], "source_datasets": [], "task_categories": ["text-to-image"], "task_ids": [], "pretty_name": "SMG-NFT", "tags": []} | 2022-10-04T18:31:50+00:00 | [] | [
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|
# Dataset Card for SMG-NFT
## Examples
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ef1661775d746e0844b299164773db733bdc0bf6 | # Dataset Card for [Dataset Name]
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-str... | sbx/superlim-2 | [
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"task_id... | 2022-09-30T11:21:49+00:00 | {"annotations_creators": ["other"], "language_creators": ["other"], "language": ["sv"], "license": [], "multilinguality": ["monolingual"], "size_categories": ["unknown"], "source_datasets": [], "task_categories": ["multiple-choice", "text-classification", "question-answering", "sentence-similarity", "token-classificati... | 2023-10-12T07:10:39+00:00 | [] | [
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## Table of Contents
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3655d3cbaad4028f787282b2ada55967aabac9c1 |
# Dataset Card for NIH Chest X-ray dataset
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields]... | alkzar90/NIH-Chest-X-ray-dataset | [
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========================================
Table of Contents
-----------------
* Table of Contents
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+ Data Fields
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... | [
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aa33b87297442d3bf9aa64ac8db2f1f14bd76b4f |
# Dataset Card for "XL-Sum-FI"
## Table of Contents
- [Dataset Card Creation Guide](#dataset-card-creation-guide)
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderbo... | TurkuNLP/xlsum-fi | [
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"conditional-text-generatio... | 2022-09-30T12:10:05+00:00 | {"annotations_creators": ["found"], "language_creators": ["machine translated"], "language": ["fi"], "license": ["cc-by-nc-sa-4.0"], "multilinguality": ["monolingual"], "size_categories": ["10K<n<100K"], "source_datasets": ["xlsum"], "task_categories": ["summarization", "text2text-generation"], "task_ids": [], "pretty_... | 2022-10-25T05:30:19+00:00 | [] | [
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|
# Dataset Card for "XL-Sum-FI"
## Table of Contents
- Dataset Card Creation Guide
- Table of Contents
- Dataset Description
- Dataset Summary
- Supported Tasks and Leaderboards
- Languages
- Dataset Structure
- Data Instances
- Data Fields
- Data Splits
- Dataset Creation
- Curatio... | [
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5e63d4fc3c1140553c27f8db01e881011147b0b6 | This dataset was pushed to Hub through the UI. | Besedo/random-dataset-10000 | [
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882bcea9e7a2a6c83e55fee2f9021b4bdf4f95f2 | This dataset was programmatically uploaded to this repo using huggingface-hub Python API | Besedo/random-dataset-1000000 | [
"region:us"
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27624246741bea210f5f437820169dc2e39d41d4 |
# Dataset Card for MSMARCO - Natural Language Generation Task
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Da... | din0s/msmarco-nlgen | [
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===========================================================
Table of Contents
-----------------
* Table of Contents
* Dataset Description
+ Dataset Summary
+ Supported Tasks and Leaderboards
+ Languages
* Dataset Structure
+ Data Instances
+ Data Fiel... | [
"### Dataset Summary\n\n\nThe original focus of MSMARCO was to provide a corpus for training and testing systems which given a real domain user query systems would then provide the most likley candidate answer and do so in language which was natural and conversational. All questions have been generated from real an... | [
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5e3ddde521c24727a134e4825d2927de25784c41 |
# Dataset Card for Lipogram-e
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-struc... | Hellisotherpeople/Lipogram-e | [
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"la... | 2022-09-30T16:04:19+00:00 | {"annotations_creators": ["no-annotation"], "language_creators": ["expert-generated"], "language": ["en"], "license": ["mit"], "multilinguality": ["monolingual"], "size_categories": ["100K<n<1M"], "source_datasets": ["original"], "task_categories": ["text-generation", "fill-mask"], "task_ids": ["language-modeling", "ma... | 2022-09-30T17:04:43+00:00 | [] | [
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# Dataset Card for Lipogram-e
## Table of Contents
- Table of Contents
- Dataset Description
- Dataset Summary
- Supported Tasks and Leaderboards
- Languages
- Dataset Structure
- Data Instances
- Data Fields
- Data Splits
- Dataset Creation
- Curation Rationale
- Source Data
- Annotations
- Pers... | [
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d3264617542ec95d20eab292cb2b227beacc3c53 | # Dataset Card for "lener_br_finetuning_language_model"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | luciolrv/lener_br_finetuning_language_model | [
"region:us"
] | 2022-09-30T20:46:00+00:00 | {"dataset_info": {"features": [{"name": "text", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 1544086, "num_examples": 2659}, {"name": "validation", "num_bytes": 284559, "num_examples": 665}], "download_size": 1013297, "dataset_size": 1828645}} | 2023-06-11T14:57:37+00:00 | [] | [] | TAGS
#region-us
| # Dataset Card for "lener_br_finetuning_language_model"
More Information needed | [
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c797997d442273e284644de093e2e4ff9419632a |
# Dataset Card for "lmqg/qg_frquad"
***IMPORTANT***: This is a dummy dataset for [lmqg/qg_frquad](https://huggingface.co/datasets/lmqg/qg_frquad). The original FRQuAD requires to fill a form (https://fquad.illuin.tech/) to get the data, and our lmqg/qg_frquad follows FQuAD's license. If you need lmqg/qg_frquad, please... | lmqg/qg_frquad_dummy | [
"task_categories:text2text-generation",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:fquad",
"language:fr",
"license:cc-by-4.0",
"question-generation",
"arxiv:2210.03992",
"region:us"
] | 2022-09-30T22:10:39+00:00 | {"language": "fr", "license": "cc-by-4.0", "multilinguality": "monolingual", "size_categories": "10K<n<100K", "source_datasets": "fquad", "task_categories": ["text2text-generation"], "task_ids": [], "pretty_name": "FQuAD for question generation", "tags": ["question-generation"]} | 2022-11-05T03:05:12+00:00 | [
"2210.03992"
] | [
"fr"
] | TAGS
#task_categories-text2text-generation #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-fquad #language-French #license-cc-by-4.0 #question-generation #arxiv-2210.03992 #region-us
| Dataset Card for "lmqg/qg\_frquad"
==================================
*IMPORTANT*: This is a dummy dataset for lmqg/qg\_frquad. The original FRQuAD requires to fill a form (URL to get the data, and our lmqg/qg\_frquad follows FQuAD's license. If you need lmqg/qg\_frquad, please first request the access to FQuAD on th... | [
"### Dataset Summary\n\n\nThis is a subset of QG-Bench, a unified question generation benchmark proposed in\n\"Generative Language Models for Paragraph-Level Question Generation: A Unified Benchmark and Evaluation, EMNLP 2022 main conference\".\nThis is a modified version of FQuAD for question generation (QG) task.... | [
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5631a9bd17a096bab2cd02ea23adbf2327db0d91 | # namu.wiki database dump
##
https://namu.wiki/ database dump 2022/03/01<br/>
- 867024 rows
- download size: 3GB
## Usage
```bash
pip install datasets
```
```python
from datasets import load_dataset
dataset = load_dataset("heegyu/namuwiki")
print(dataset["train"][0])
```
```
{'title': '!!아앗!!',
'text': '\n[목차]\n\n... | heegyu/namuwiki | [
"task_categories:other",
"language_creators:other",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"language:ko",
"license:cc-by-nc-sa-2.0",
"region:us"
] | 2022-09-30T23:40:12+00:00 | {"language_creators": ["other"], "language": ["ko"], "license": "cc-by-nc-sa-2.0", "multilinguality": ["monolingual"], "size_categories": ["100K<n<1M"], "task_categories": ["other"]} | 2022-10-01T01:40:40+00:00 | [] | [
"ko"
] | TAGS
#task_categories-other #language_creators-other #multilinguality-monolingual #size_categories-100K<n<1M #language-Korean #license-cc-by-nc-sa-2.0 #region-us
| # URL database dump
##
URL database dump 2022/03/01<br/>
- 867024 rows
- download size: 3GB
## Usage
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] |
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