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Sebasloco/frida_arellano | Sebasloco | 2022-10-16T00:50:52Z | 15 | 0 | null | [
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seraldu/sergio_prueba | seraldu | 2022-10-16T08:02:35Z | 15 | 0 | null | [
"license:bigscience-openrail-m",
"region:us"
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license: bigscience-openrail-m
---
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autoevaluate/autoeval-eval-lener_br-lener_br-39d19a-1775961623 | autoevaluate | 2022-10-16T11:37:33Z | 15 | 0 | null | [
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type: predictions
tags:
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datasets:
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eval_info:
task: entity_extraction
model: Luciano/bertimbau-base-lener-br-finetuned-lener-br
metrics: []
dataset_name: lener_br
dataset_config: lener_br
dataset_split: test
col_mapping:
tokens: tokens
tags: ner_tags
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Token Classification
* Model: Luciano/bertimbau-base-lener-br-finetuned-lener-br
* Dataset: lener_br
* Config: lener_br
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@Luciano](https://huggingface.co/Luciano) for evaluating this model. | [
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autoevaluate/autoeval-eval-lener_br-lener_br-b36dee-1776161639 | autoevaluate | 2022-10-16T12:08:13Z | 15 | 0 | null | [
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type: predictions
tags:
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eval_info:
task: entity_extraction
model: Luciano/bertimbau-base-lener-br-finetuned-lener-br
metrics: []
dataset_name: lener_br
dataset_config: lener_br
dataset_split: validation
col_mapping:
tokens: tokens
tags: ner_tags
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Token Classification
* Model: Luciano/bertimbau-base-lener-br-finetuned-lener-br
* Dataset: lener_br
* Config: lener_br
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@Luciano](https://huggingface.co/Luciano) for evaluating this model. | [
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autoevaluate/autoeval-eval-lener_br-lener_br-c186f5-1776861659 | autoevaluate | 2022-10-16T12:51:17Z | 15 | 0 | null | [
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"region:us"
] | 2022-10-16T12:51:17Z | 2022-10-16T12:48:37.000Z | 2022-10-16T12:48:37 | ---
type: predictions
tags:
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datasets:
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eval_info:
task: entity_extraction
model: Luciano/bertimbau-base-lener_br
metrics: []
dataset_name: lener_br
dataset_config: lener_br
dataset_split: train
col_mapping:
tokens: tokens
tags: ner_tags
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Token Classification
* Model: Luciano/bertimbau-base-lener_br
* Dataset: lener_br
* Config: lener_br
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@Luciano](https://huggingface.co/Luciano) for evaluating this model. | [
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autoevaluate/autoeval-eval-lener_br-lener_br-c186f5-1776861662 | autoevaluate | 2022-10-16T12:52:40Z | 15 | 0 | null | [
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"region:us"
] | 2022-10-16T12:52:40Z | 2022-10-16T12:48:47.000Z | 2022-10-16T12:48:47 | ---
type: predictions
tags:
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datasets:
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eval_info:
task: entity_extraction
model: Luciano/xlm-roberta-large-finetuned-lener-br
metrics: []
dataset_name: lener_br
dataset_config: lener_br
dataset_split: train
col_mapping:
tokens: tokens
tags: ner_tags
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Token Classification
* Model: Luciano/xlm-roberta-large-finetuned-lener-br
* Dataset: lener_br
* Config: lener_br
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@Luciano](https://huggingface.co/Luciano) for evaluating this model. | [
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Eddiefloat/dataset2 | Eddiefloat | 2022-10-16T13:11:09Z | 15 | 0 | null | [
"region:us"
] | 2022-10-16T13:11:09Z | 2022-10-16T12:53:49.000Z | 2022-10-16T12:53:49 | Entry not found | [
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iflath/LauraFlathArt | iflath | 2022-10-16T13:12:41Z | 15 | 0 | null | [
"region:us"
] | 2022-10-16T13:12:41Z | 2022-10-16T13:11:52.000Z | 2022-10-16T13:11:52 | Entry not found | [
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autoevaluate/autoeval-eval-lener_br-lener_br-280a5d-1776961678 | autoevaluate | 2022-10-16T13:19:26Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-10-16T13:19:26Z | 2022-10-16T13:18:37.000Z | 2022-10-16T13:18:37 | ---
type: predictions
tags:
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datasets:
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eval_info:
task: entity_extraction
model: pierreguillou/ner-bert-base-cased-pt-lenerbr
metrics: []
dataset_name: lener_br
dataset_config: lener_br
dataset_split: test
col_mapping:
tokens: tokens
tags: ner_tags
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Token Classification
* Model: pierreguillou/ner-bert-base-cased-pt-lenerbr
* Dataset: lener_br
* Config: lener_br
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@Luciano](https://huggingface.co/Luciano) for evaluating this model. | [
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autoevaluate/autoeval-eval-lener_br-lener_br-2a71c5-1777061680 | autoevaluate | 2022-10-16T13:19:34Z | 15 | 0 | null | [
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] | 2022-10-16T13:19:34Z | 2022-10-16T13:18:50.000Z | 2022-10-16T13:18:50 | ---
type: predictions
tags:
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datasets:
- lener_br
eval_info:
task: entity_extraction
model: pierreguillou/ner-bert-base-cased-pt-lenerbr
metrics: []
dataset_name: lener_br
dataset_config: lener_br
dataset_split: validation
col_mapping:
tokens: tokens
tags: ner_tags
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Token Classification
* Model: pierreguillou/ner-bert-base-cased-pt-lenerbr
* Dataset: lener_br
* Config: lener_br
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@Luciano](https://huggingface.co/Luciano) for evaluating this model. | [
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autoevaluate/autoeval-eval-lener_br-lener_br-2a71c5-1777061681 | autoevaluate | 2022-10-16T13:20:02Z | 15 | 0 | null | [
"autotrain",
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"region:us"
] | 2022-10-16T13:20:02Z | 2022-10-16T13:18:58.000Z | 2022-10-16T13:18:58 | ---
type: predictions
tags:
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datasets:
- lener_br
eval_info:
task: entity_extraction
model: pierreguillou/ner-bert-large-cased-pt-lenerbr
metrics: []
dataset_name: lener_br
dataset_config: lener_br
dataset_split: validation
col_mapping:
tokens: tokens
tags: ner_tags
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Token Classification
* Model: pierreguillou/ner-bert-large-cased-pt-lenerbr
* Dataset: lener_br
* Config: lener_br
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@Luciano](https://huggingface.co/Luciano) for evaluating this model. | [
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autoevaluate/autoeval-eval-lener_br-lener_br-851daf-1777161682 | autoevaluate | 2022-10-16T13:21:40Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-10-16T13:21:40Z | 2022-10-16T13:19:04.000Z | 2022-10-16T13:19:04 | ---
type: predictions
tags:
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datasets:
- lener_br
eval_info:
task: entity_extraction
model: pierreguillou/ner-bert-base-cased-pt-lenerbr
metrics: []
dataset_name: lener_br
dataset_config: lener_br
dataset_split: train
col_mapping:
tokens: tokens
tags: ner_tags
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Token Classification
* Model: pierreguillou/ner-bert-base-cased-pt-lenerbr
* Dataset: lener_br
* Config: lener_br
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@Luciano](https://huggingface.co/Luciano) for evaluating this model. | [
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autoevaluate/autoeval-eval-lener_br-lener_br-851daf-1777161683 | autoevaluate | 2022-10-16T13:22:52Z | 15 | 0 | null | [
"autotrain",
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"region:us"
] | 2022-10-16T13:22:52Z | 2022-10-16T13:19:11.000Z | 2022-10-16T13:19:11 | ---
type: predictions
tags:
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datasets:
- lener_br
eval_info:
task: entity_extraction
model: pierreguillou/ner-bert-large-cased-pt-lenerbr
metrics: []
dataset_name: lener_br
dataset_config: lener_br
dataset_split: train
col_mapping:
tokens: tokens
tags: ner_tags
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Token Classification
* Model: pierreguillou/ner-bert-large-cased-pt-lenerbr
* Dataset: lener_br
* Config: lener_br
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@Luciano](https://huggingface.co/Luciano) for evaluating this model. | [
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KJM/Textual_inversion | KJM | 2022-10-16T13:53:01Z | 15 | 0 | null | [
"region:us"
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Harsit/xnli2.0_train_german | Harsit | 2022-10-16T14:26:06Z | 15 | 0 | null | [
"region:us"
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marcelarosalesj/crowdsourced-build-a-movie-poster-demo | marcelarosalesj | 2022-10-16T18:24:19Z | 15 | 0 | null | [
"region:us"
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tiagoblima/punctuation-nilc-t5 | tiagoblima | 2022-11-13T18:07:55Z | 15 | 0 | null | [
"region:us"
] | 2022-11-13T18:07:55Z | 2022-10-16T17:02:13.000Z | 2022-10-16T17:02:13 | ---
dataset_info:
features:
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dataset_size: 6042502.196980659
---
# Dataset Card for "punctuation-nilc-t5"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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tiagoblima/punctuation-nilc-bert | tiagoblima | 2023-07-19T17:03:29Z | 15 | 0 | null | [
"language:pt",
"region:us"
] | 2023-07-19T17:03:29Z | 2022-10-16T18:02:29.000Z | 2022-10-16T18:02:29 | ---
language: pt
dataset_info:
features:
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dtype: int64
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dtype: string
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dtype: string
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num_examples: 9371
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num_bytes: 479472.5920696906
num_examples: 1041
download_size: 1802076
dataset_size: 5882150.366469645
---
# Dataset Card for "punctuation-nilc"
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dhm99/images | dhm99 | 2022-10-17T00:15:30Z | 15 | 0 | null | [
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w0lfandbehem0th/test-images | w0lfandbehem0th | 2022-10-17T03:46:04Z | 15 | 0 | null | [
"license:apache-2.0",
"region:us"
] | 2022-10-17T03:46:04Z | 2022-10-17T03:35:15.000Z | 2022-10-17T03:35:15 | ---
license: apache-2.0
---
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cjvt/sloie | cjvt | 2022-10-21T07:36:18Z | 15 | 0 | null | [
"task_categories:text-classification",
"task_categories:token-classification",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"size_categories:100K<n<1M",
"language:sl",
"license:cc-by-nc-sa-4.0",
"idiom-detection",
... | 2022-10-21T07:36:18Z | 2022-10-17T12:55:41.000Z | 2022-10-17T12:55:41 | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- sl
license:
- cc-by-nc-sa-4.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
- 100K<n<1M
source_datasets: []
task_categories:
- text-classification
- token-classification
task_ids: []
pretty_name: Dataset of Slovene idiomatic expressions SloIE
tags:
- idiom-detection
- multiword-expression-detection
---
# Dataset Card for SloIE
### Dataset Summary
SloIE is a manually labelled dataset of Slovene idiomatic expressions. It contains 29399 sentences with 75 different expressions that can occur with either a literal or an idiomatic meaning, with appropriate manual annotations for each token. The idiomatic expressions were selected from the [Slovene Lexical Database]( (http://hdl.handle.net/11356/1030). Only expressions that can occur with both a literal and an idiomatic meaning were selected. The sentences were extracted from the Gigafida corpus.
For a more detailed description of the dataset, please see the paper Škvorc et al. (2022) - see below.
### Supported Tasks and Leaderboards
Idiom detection.
### Languages
Slovenian.
## Dataset Structure
### Data Instances
A sample instance from the dataset:
```json
{
'sentence': 'Fantje regljajo v enem kotu, deklice pa svoje obrazke barvajo s pisanimi barvami.',
'expression': 'barvati kaj s črnimi barvami',
'word_order': [11, 10, 12, 13, 14],
'sentence_words': ['Fantje', 'regljajo', 'v', 'enem', 'kotu,', 'deklice', 'pa', 'svoje', 'obrazke', 'barvajo', 's', 'pisanimi', 'barvami.'],
'is_idiom': ['*', '*', '*', '*', '*', '*', '*', '*', 'NE', 'NE', 'NE', 'NE', 'NE']
}
```
In this `sentence`, the words of the expression "barvati kaj s črnimi barvami" are used in a literal sense, as indicated by the "NE" annotations inside `is_idiom`. The "*" annotations indicate the words are not part of the expression.
### Data Fields
- `sentence`: raw sentence in string form - **WARNING**: this is at times slightly different from the words inside `sentence_words` (e.g., "..." here could be "." in `sentence_words`);
- `expression`: the annotated idiomatic expression;
- `word_order`: numbers indicating the positions of tokens that belong to the expression;
- `sentence_words`: words in the sentence;
- `is_idiom`: a string denoting whether each word has an idiomatic (`"DA"`), literal (`"NE"`), or ambiguous (`"NEJASEN ZGLED"`) meaning. `"*"` means that the word is not part of the expression.
## Additional Information
### Dataset Curators
Tadej Škvorc, Polona Gantar, Marko Robnik-Šikonja.
### Licensing Information
CC BY-NC-SA 4.0.
### Citation Information
```
@article{skvorc2022mice,
title = {MICE: Mining Idioms with Contextual Embeddings},
journal = {Knowledge-Based Systems},
volume = {235},
pages = {107606},
year = {2022},
doi = {https://doi.org/10.1016/j.knosys.2021.107606},
url = {https://www.sciencedirect.com/science/article/pii/S0950705121008686},
author = {{\v S}kvorc, Tadej and Gantar, Polona and Robnik-{\v S}ikonja, Marko},
}
```
### Contributions
Thanks to [@matejklemen](https://github.com/matejklemen) for adding this dataset.
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nayan06/conversion1.0 | nayan06 | 2022-10-18T10:40:06Z | 15 | 0 | null | [
"region:us"
] | 2022-10-18T10:40:06Z | 2022-10-18T06:44:35.000Z | 2022-10-18T06:44:35 | ---
train-eval-index:
- config: default
task: text-classification
task_id: multi_class_classification
splits:
eval_split: test
col_mapping:
text: text
label: target
--- | [
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autoevaluate/autoeval-eval-emotion-default-1b690b-1797662163 | autoevaluate | 2022-10-18T06:55:22Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-10-18T06:55:22Z | 2022-10-18T06:54:54.000Z | 2022-10-18T06:54:54 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- emotion
eval_info:
task: multi_class_classification
model: Emanuel/bertweet-emotion-base
metrics: []
dataset_name: emotion
dataset_config: default
dataset_split: test
col_mapping:
text: text
target: label
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Multi-class Text Classification
* Model: Emanuel/bertweet-emotion-base
* Dataset: emotion
* Config: default
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@nayan06](https://huggingface.co/nayan06) for evaluating this model. | [
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maximilienroberti/test_2 | maximilienroberti | 2022-11-06T15:53:53Z | 15 | 0 | null | [
"region:us"
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autoevaluate/autoeval-eval-phpthinh__ex3-all-630c04-1799362235 | autoevaluate | 2022-10-18T09:07:43Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
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type: predictions
tags:
- autotrain
- evaluation
datasets:
- phpthinh/ex3
eval_info:
task: text_zero_shot_classification
model: bigscience/bloom-560m
metrics: []
dataset_name: phpthinh/ex3
dataset_config: all
dataset_split: test
col_mapping:
text: text
classes: classes
target: target
---
# 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: bigscience/bloom-560m
* Dataset: phpthinh/ex3
* Config: all
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@phpthinh](https://huggingface.co/phpthinh) for evaluating this model. | [
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Osaleh/Intents | Osaleh | 2022-10-18T09:52:27Z | 15 | 0 | null | [
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Osaleh/Intent_1018 | Osaleh | 2022-10-18T09:58:45Z | 15 | 0 | null | [
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"region:us"
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DavidCDZ/AdavidCDZ | DavidCDZ | 2022-10-18T12:55:40Z | 15 | 0 | null | [
"region:us"
] | 2022-10-18T12:55:40Z | 2022-10-18T12:52:32.000Z | 2022-10-18T12:52:32 | Entry not found | [
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Kentaline/hf-dataset-study | Kentaline | 2022-10-18T14:35:42Z | 15 | 0 | null | [
"license:other",
"region:us"
] | 2022-10-18T14:35:42Z | 2022-10-18T13:49:15.000Z | 2022-10-18T13:49:15 | ---
license: other
---
---
annotations_creators:
- crowdsourced
language:
- ja
language_creators:
- crowdsourced
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
paperswithcode_id: squad
pretty_name: squad-ja
size_categories:
- 100K<n<1M
source_datasets:
- original
tags: []
task_categories:
- question-answering
task_ids:
- open-domain-qa
- extractive-qa
train-eval-index:
- col_mapping:
answers:
answer_start: answer_start
text: text
context: context
question: question
config: squad_v2
metrics:
- name: SQuAD v2
type: squad_v2
splits:
eval_split: validation
train_split: train
task: question-answering
task_id: extractive_question_answering
---
# 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-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
- **Homepage:**
- **Repository:**
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
Google翻訳APIで翻訳した日本語版SQuAD2.0
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
Japanese
## Dataset Structure
### Data Instances
```
{
"start": 43,
"end": 88,
"question": "ビヨンセ は いつ から 人気 を 博し 始め ました か ？",
"context": "BeyoncéGiselleKnowles - Carter （ /b i ː ˈ j ɒ nse ɪ / bee - YON - say ） （ 1981 年 9 月 4 日 生まれ ） は 、 アメリカ の シンガー 、 ソング ライター 、 レコード プロデューサー 、 女優 です 。 テキサス 州 ヒューストン で 生まれ育った 彼女 は 、 子供 の 頃 に さまざまな 歌 と 踊り の コンテスト に 出演 し 、 1990 年 代 後半 に R ＆ B ガールグループ Destiny & 39 ; sChild の リード シンガー と して 名声 を 博し ました 。 父親 の マシューノウルズ が 管理 する この グループ は 、 世界 で 最も 売れて いる 少女 グループ の 1 つ に なり ました 。 彼 ら の 休み は ビヨンセ の デビュー アルバム 、 DangerouslyinLove （ 2003 ） の リリース を 見 ました 。 彼女 は 世界 中 で ソロ アーティスト と して 確立 し 、 5 つ の グラミー 賞 を 獲得 し 、 ビル ボード ホット 100 ナンバーワン シングル 「 CrazyinLove 」 と 「 BabyBoy 」 を フィーチャー し ました 。",
"id": "56be85543aeaaa14008c9063"
}
```
### Data Fields
- start
- end
- question
- context
- id
### Data Splits
- train 86820
- valid 5927
## Dataset Creation
### Curation Rationale
[More Information Needed]
### Source Data
#### Initial Data Collection and Normalization
[More Information Needed]
#### Who are the source language producers?
[More Information Needed]
### Annotations
#### Annotation process
[More Information Needed]
#### Who are the annotators?
[More Information Needed]
### Personal and Sensitive Information
[More Information Needed]
## Considerations for Using the Data
### Social Impact of Dataset
[More Information Needed]
### Discussion of Biases
[More Information Needed]
### Other Known Limitations
[More Information Needed]
## Additional Information
### Dataset Curators
[More Information Needed]
### Licensing Information
[More Information Needed]
### Citation Information
[More Information Needed]
### Contributions
Thanks to [@github-username](https://github.com/<github-username>) for adding this dataset. | [
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DILAB-HYU/SimKoR | DILAB-HYU | 2022-10-18T17:27:05Z | 15 | 3 | null | [
"license:cc-by-4.0",
"region:us"
] | 2022-10-18T17:27:05Z | 2022-10-18T14:51:49.000Z | 2022-10-18T14:51:49 | ---
license: cc-by-4.0
---
# SimKoR
We provide korean sentence text similarity pair dataset using sentiment analysis corpus from [bab2min/corpus](https://github.com/bab2min/corpus).
This data crawling korean review from naver shopping website. we reconstruct subset of dataset to make our dataset.
## Dataset description
The original dataset description can be found at the link [[here]](https://github.com/bab2min/corpus/tree/master/sentiment).
In korean Contrastive Learning, There are few suitable validation dataset (only KorNLI). To create contrastive learning validation dataset, we changed original sentiment analysis dataset to sentence text similar dataset. Our simkor dataset was created by grouping pair of sentence. Each score [0,1,2,4,5] means how far the meaning is between sentences.
## Data Distribution
Our dataset class consist of text similarity score [0, 1,2,4,5]. each score consists of data of the same size.
<table>
<tr><th>Score</th><th>train</th><th>valid</th><th>test</th></tr>
<tr><th>5</th><th>4,000</th><th>1,000</th><th>1,000</th></tr>
<tr><th>4</th><th>4,000</th><th>1,000</th><th>1,000</th></tr>
<tr><th>2</th><th>4,000</th><th>1,000</th><th>1,000</th></tr>
<tr><th>1</th><th>4,000</th><th>1,000</th><th>1,000</th></tr>
<tr><th>0</th><th>4,000</th><th>1,000</th><th>1,000</th></tr>
<tr><th>All</th><th>20,000</th><th>5,000</th><th>5,000</th></tr>
</table>
## Example
```
text1 text2 label
고속충전이 안됨ㅠㅠ 집에매연냄새없앨려했는데 그냥창문여는게더 공기가좋네요 5
적당히 맵고 괜찮네요 어제 시킨게 벌써 왔어요 ㅎㅎ 배송빠르고 품질양호합니다 4
다 괜찮은데 배송이 10일이나 걸린게 많이 아쉽네요. 선반 설치하고 나니 주방 베란다 완전 다시 태어났어요~ 2
가격 싸지만 쿠션이 약해 무릎 아파요~ 반품하려구요~ 튼튼하고 빨래도 많이 걸 수 있고 잘쓰고 있어요 1
각인이 찌그저져있고 엉성합니다. 처음 해보는 방탈출이었는데 너무 재미있었어요. 0
```
## Contributors
The main contributors of the work are :
- [Jaemin Kim](https://github.com/kimfunn)\*
- [Yohan Na](https://github.com/nayohan)\*
- [Kangmin Kim](https://github.com/Gangsss)
- [Sangrak Lee](https://github.com/PangRAK)
\*: Equal Contribution
Hanyang University Data Intelligence Lab[(DILAB)](http://dilab.hanyang.ac.kr/) providing support ❤️
## Github
- **Repository :** [SimKoR](https://github.com/nayohan/SimKoR)
## License
<a rel="license" href="http://creativecommons.org/licenses/by-sa/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by-sa/4.0/88x31.png" /></a>This work is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by-sa/4.0/">Creative Commons Attribution-ShareAlike 4.0 International License</a>. | [
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mrm8488/stackoverflow-ner | mrm8488 | 2022-10-18T14:55:17Z | 15 | 0 | null | [
"region:us"
] | 2022-10-18T14:55:17Z | 2022-10-18T14:55:02.000Z | 2022-10-18T14:55:02 | ---
dataset_info:
features:
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sequence: string
- name: ner_tags
sequence: string
splits:
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num_bytes: 680079
num_examples: 3108
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num_bytes: 2034117
num_examples: 9263
- name: validation
num_bytes: 640935
num_examples: 2936
download_size: 692070
dataset_size: 3355131
---
# Dataset Card for "stackoverflow-ner"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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license: bsd
---
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spacemanidol/orcas | spacemanidol | 2022-10-18T19:44:24Z | 15 | 0 | null | [
"license:mit",
"region:us"
] | 2022-10-18T19:44:24Z | 2022-10-18T19:39:05.000Z | 2022-10-18T19:39:05 | ---
license: mit
---
| [
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nitrosocke/arcane-diffusion-dataset | nitrosocke | 2022-10-18T20:58:23Z | 15 | 11 | null | [
"license:creativeml-openrail-m",
"region:us"
] | 2022-10-18T20:58:23Z | 2022-10-18T20:47:20.000Z | 2022-10-18T20:47:20 | ---
license: creativeml-openrail-m
---
# Arcane Diffusion Dataset
Dataset containing the 75 images used to train the [Arcane Diffusion](https://huggingface.co/nitrosocke/Arcane-Diffusion) model.
Settings for training:
```class prompt: illustration style
instance prompt: illustration arcane style
learning rate: 5e-6
lr scheduler: constant
num class images: 1000
max train steps: 5000
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joey234/sar | joey234 | 2022-10-19T00:37:02Z | 15 | 0 | null | [
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autoevaluate/autoeval-eval-cnn_dailymail-3.0.0-2bc9e0-1812262541 | autoevaluate | 2022-10-19T07:36:46Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-10-19T07:36:46Z | 2022-10-19T05:49:28.000Z | 2022-10-19T05:49:28 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- cnn_dailymail
eval_info:
task: summarization
model: google/pegasus-cnn_dailymail
metrics: ['bleu']
dataset_name: cnn_dailymail
dataset_config: 3.0.0
dataset_split: test
col_mapping:
text: article
target: highlights
---
# 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: google/pegasus-cnn_dailymail
* Dataset: cnn_dailymail
* Config: 3.0.0
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@DongfuTingle](https://huggingface.co/DongfuTingle) for evaluating this model. | [
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Menahem/sv_corpora_parliament_processed | Menahem | 2022-10-19T11:15:12Z | 15 | 0 | null | [
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dataset_info:
features:
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dtype: string
splits:
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download_size: 158940469
dataset_size: 292351437
---
# Dataset Card for "sv_corpora_parliament_processed"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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dataset_size: 830655900
---
# Dataset Card for "CelebA-faces-cropped-128-encoded"
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research-backup/semeval2012_relational_similarity_v3 | research-backup | 2022-10-21T10:17:28Z | 15 | 0 | null | [
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language:
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license:
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multilinguality:
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size_categories:
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pretty_name: SemEval2012 task 2 Relational Similarity
---
# Dataset Card for "relbert/semeval2012_relational_similarity_v3"
## Dataset Description
- **Repository:** [RelBERT](https://github.com/asahi417/relbert)
- **Paper:** [https://aclanthology.org/S12-1047/](https://aclanthology.org/S12-1047/)
- **Dataset:** SemEval2012: Relational Similarity
### Dataset Summary
***IMPORTANT***: This is the same dataset as [relbert/semeval2012_relational_similarity](https://huggingface.co/datasets/relbert/semeval2012_relational_similarity),
but with a different dataset construction.
Relational similarity dataset from [SemEval2012 task 2](https://aclanthology.org/S12-1047/), compiled to fine-tune [RelBERT](https://github.com/asahi417/relbert) model.
The dataset contains a list of positive and negative word pair from 89 pre-defined relations.
The relation types are constructed on top of following 10 parent relation types.
```shell
{
1: "Class Inclusion", # Hypernym
2: "Part-Whole", # Meronym, Substance Meronym
3: "Similar", # Synonym, Co-hypornym
4: "Contrast", # Antonym
5: "Attribute", # Attribute, Event
6: "Non Attribute",
7: "Case Relation",
8: "Cause-Purpose",
9: "Space-Time",
10: "Representation"
}
```
Each of the parent relation is further grouped into child relation types where the definition can be found [here](https://drive.google.com/file/d/0BzcZKTSeYL8VenY0QkVpZVpxYnc/view?resourcekey=0-ZP-UARfJj39PcLroibHPHw).
## Dataset Structure
### Data Instances
An example of `train` looks as follows.
```
{
'relation_type': '8d',
'positives': [ [ "breathe", "live" ], [ "study", "learn" ], [ "speak", "communicate" ], ... ]
'negatives': [ [ "starving", "hungry" ], [ "clean", "bathe" ], [ "hungry", "starving" ], ... ]
}
```
### Data Splits
| name |train|validation|
|---------|----:|---------:|
|semeval2012_relational_similarity| 89 | 89|
### Number of Positive/Negative Word-pairs in each Split
| | positives | negatives |
|:--------------------------------------------|------------:|------------:|
| ('1', 'parent', 'train') | 110 | 680 |
| ('1', 'parent', 'validation') | 129 | 760 |
| ('10', 'parent', 'train') | 60 | 730 |
| ('10', 'parent', 'validation') | 66 | 823 |
| ('10a', 'child', 'train') | 10 | 780 |
| ('10a', 'child', 'validation') | 14 | 875 |
| ('10a', 'child_prototypical', 'train') | 39 | 506 |
| ('10a', 'child_prototypical', 'validation') | 63 | 938 |
| ('10b', 'child', 'train') | 10 | 780 |
| ('10b', 'child', 'validation') | 13 | 876 |
| ('10b', 'child_prototypical', 'train') | 39 | 428 |
| ('10b', 'child_prototypical', 'validation') | 57 | 707 |
| ('10c', 'child', 'train') | 10 | 780 |
| ('10c', 'child', 'validation') | 11 | 878 |
| ('10c', 'child_prototypical', 'train') | 39 | 545 |
| ('10c', 'child_prototypical', 'validation') | 45 | 650 |
| ('10d', 'child', 'train') | 10 | 780 |
| ('10d', 'child', 'validation') | 10 | 879 |
| ('10d', 'child_prototypical', 'train') | 39 | 506 |
| ('10d', 'child_prototypical', 'validation') | 39 | 506 |
| ('10e', 'child', 'train') | 10 | 780 |
| ('10e', 'child', 'validation') | 8 | 881 |
| ('10e', 'child_prototypical', 'train') | 39 | 350 |
| ('10e', 'child_prototypical', 'validation') | 27 | 218 |
| ('10f', 'child', 'train') | 10 | 780 |
| ('10f', 'child', 'validation') | 10 | 879 |
| ('10f', 'child_prototypical', 'train') | 39 | 506 |
| ('10f', 'child_prototypical', 'validation') | 39 | 506 |
| ('1a', 'child', 'train') | 10 | 780 |
| ('1a', 'child', 'validation') | 14 | 875 |
| ('1a', 'child_prototypical', 'train') | 39 | 428 |
| ('1a', 'child_prototypical', 'validation') | 63 | 812 |
| ('1b', 'child', 'train') | 10 | 780 |
| ('1b', 'child', 'validation') | 14 | 875 |
| ('1b', 'child_prototypical', 'train') | 39 | 428 |
| ('1b', 'child_prototypical', 'validation') | 63 | 812 |
| ('1c', 'child', 'train') | 10 | 780 |
| ('1c', 'child', 'validation') | 11 | 878 |
| ('1c', 'child_prototypical', 'train') | 39 | 545 |
| ('1c', 'child_prototypical', 'validation') | 45 | 650 |
| ('1d', 'child', 'train') | 10 | 780 |
| ('1d', 'child', 'validation') | 16 | 873 |
| ('1d', 'child_prototypical', 'train') | 39 | 428 |
| ('1d', 'child_prototypical', 'validation') | 75 | 1040 |
| ('1e', 'child', 'train') | 10 | 780 |
| ('1e', 'child', 'validation') | 8 | 881 |
| ('1e', 'child_prototypical', 'train') | 39 | 311 |
| ('1e', 'child_prototypical', 'validation') | 27 | 191 |
| ('2', 'parent', 'train') | 100 | 690 |
| ('2', 'parent', 'validation') | 117 | 772 |
| ('2a', 'child', 'train') | 10 | 780 |
| ('2a', 'child', 'validation') | 15 | 874 |
| ('2a', 'child_prototypical', 'train') | 39 | 506 |
| ('2a', 'child_prototypical', 'validation') | 69 | 1061 |
| ('2b', 'child', 'train') | 10 | 780 |
| ('2b', 'child', 'validation') | 11 | 878 |
| ('2b', 'child_prototypical', 'train') | 39 | 389 |
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| ('2c', 'child', 'validation') | 13 | 876 |
| ('2c', 'child_prototypical', 'train') | 39 | 467 |
| ('2c', 'child_prototypical', 'validation') | 57 | 764 |
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| ('2d', 'child', 'validation') | 10 | 879 |
| ('2d', 'child_prototypical', 'train') | 39 | 467 |
| ('2d', 'child_prototypical', 'validation') | 39 | 467 |
| ('2e', 'child', 'train') | 10 | 780 |
| ('2e', 'child', 'validation') | 11 | 878 |
| ('2e', 'child_prototypical', 'train') | 39 | 506 |
| ('2e', 'child_prototypical', 'validation') | 45 | 605 |
| ('2f', 'child', 'train') | 10 | 780 |
| ('2f', 'child', 'validation') | 11 | 878 |
| ('2f', 'child_prototypical', 'train') | 39 | 623 |
| ('2f', 'child_prototypical', 'validation') | 45 | 740 |
| ('2g', 'child', 'train') | 10 | 780 |
| ('2g', 'child', 'validation') | 16 | 873 |
| ('2g', 'child_prototypical', 'train') | 39 | 389 |
| ('2g', 'child_prototypical', 'validation') | 75 | 965 |
| ('2h', 'child', 'train') | 10 | 780 |
| ('2h', 'child', 'validation') | 11 | 878 |
| ('2h', 'child_prototypical', 'train') | 39 | 506 |
| ('2h', 'child_prototypical', 'validation') | 45 | 605 |
| ('2i', 'child', 'train') | 10 | 780 |
| ('2i', 'child', 'validation') | 9 | 880 |
| ('2i', 'child_prototypical', 'train') | 39 | 545 |
| ('2i', 'child_prototypical', 'validation') | 33 | 446 |
| ('2j', 'child', 'train') | 10 | 780 |
| ('2j', 'child', 'validation') | 10 | 879 |
| ('2j', 'child_prototypical', 'train') | 39 | 584 |
| ('2j', 'child_prototypical', 'validation') | 39 | 584 |
| ('3', 'parent', 'train') | 80 | 710 |
| ('3', 'parent', 'validation') | 80 | 809 |
| ('3a', 'child', 'train') | 10 | 780 |
| ('3a', 'child', 'validation') | 11 | 878 |
| ('3a', 'child_prototypical', 'train') | 39 | 506 |
| ('3a', 'child_prototypical', 'validation') | 45 | 605 |
| ('3b', 'child', 'train') | 10 | 780 |
| ('3b', 'child', 'validation') | 11 | 878 |
| ('3b', 'child_prototypical', 'train') | 39 | 623 |
| ('3b', 'child_prototypical', 'validation') | 45 | 740 |
| ('3c', 'child', 'train') | 10 | 780 |
| ('3c', 'child', 'validation') | 12 | 877 |
| ('3c', 'child_prototypical', 'train') | 39 | 467 |
| ('3c', 'child_prototypical', 'validation') | 51 | 659 |
| ('3d', 'child', 'train') | 10 | 780 |
| ('3d', 'child', 'validation') | 14 | 875 |
| ('3d', 'child_prototypical', 'train') | 39 | 467 |
| ('3d', 'child_prototypical', 'validation') | 63 | 875 |
| ('3e', 'child', 'train') | 10 | 780 |
| ('3e', 'child', 'validation') | 5 | 884 |
| ('3e', 'child_prototypical', 'train') | 39 | 623 |
| ('3e', 'child_prototypical', 'validation') | 10 | 140 |
| ('3f', 'child', 'train') | 10 | 780 |
| ('3f', 'child', 'validation') | 11 | 878 |
| ('3f', 'child_prototypical', 'train') | 39 | 662 |
| ('3f', 'child_prototypical', 'validation') | 45 | 785 |
| ('3g', 'child', 'train') | 10 | 780 |
| ('3g', 'child', 'validation') | 6 | 883 |
| ('3g', 'child_prototypical', 'train') | 39 | 584 |
| ('3g', 'child_prototypical', 'validation') | 15 | 200 |
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| ('3h', 'child_prototypical', 'validation') | 39 | 584 |
| ('4', 'parent', 'train') | 80 | 710 |
| ('4', 'parent', 'validation') | 82 | 807 |
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| ('4a', 'child', 'validation') | 11 | 878 |
| ('4a', 'child_prototypical', 'train') | 39 | 623 |
| ('4a', 'child_prototypical', 'validation') | 45 | 740 |
| ('4b', 'child', 'train') | 10 | 780 |
| ('4b', 'child', 'validation') | 7 | 882 |
| ('4b', 'child_prototypical', 'train') | 39 | 428 |
| ('4b', 'child_prototypical', 'validation') | 21 | 203 |
| ('4c', 'child', 'train') | 10 | 780 |
| ('4c', 'child', 'validation') | 12 | 877 |
| ('4c', 'child_prototypical', 'train') | 39 | 545 |
| ('4c', 'child_prototypical', 'validation') | 51 | 761 |
| ('4d', 'child', 'train') | 10 | 780 |
| ('4d', 'child', 'validation') | 4 | 885 |
| ('4d', 'child_prototypical', 'train') | 39 | 389 |
| ('4d', 'child_prototypical', 'validation') | 6 | 46 |
| ('4e', 'child', 'train') | 10 | 780 |
| ('4e', 'child', 'validation') | 12 | 877 |
| ('4e', 'child_prototypical', 'train') | 39 | 623 |
| ('4e', 'child_prototypical', 'validation') | 51 | 863 |
| ('4f', 'child', 'train') | 10 | 780 |
| ('4f', 'child', 'validation') | 9 | 880 |
| ('4f', 'child_prototypical', 'train') | 39 | 623 |
| ('4f', 'child_prototypical', 'validation') | 33 | 512 |
| ('4g', 'child', 'train') | 10 | 780 |
| ('4g', 'child', 'validation') | 15 | 874 |
| ('4g', 'child_prototypical', 'train') | 39 | 467 |
| ('4g', 'child_prototypical', 'validation') | 69 | 992 |
| ('4h', 'child', 'train') | 10 | 780 |
| ('4h', 'child', 'validation') | 12 | 877 |
| ('4h', 'child_prototypical', 'train') | 39 | 584 |
| ('4h', 'child_prototypical', 'validation') | 51 | 812 |
| ('5', 'parent', 'train') | 90 | 700 |
| ('5', 'parent', 'validation') | 105 | 784 |
| ('5a', 'child', 'train') | 10 | 780 |
| ('5a', 'child', 'validation') | 14 | 875 |
| ('5a', 'child_prototypical', 'train') | 39 | 467 |
| ('5a', 'child_prototypical', 'validation') | 63 | 875 |
| ('5b', 'child', 'train') | 10 | 780 |
| ('5b', 'child', 'validation') | 8 | 881 |
| ('5b', 'child_prototypical', 'train') | 39 | 584 |
| ('5b', 'child_prototypical', 'validation') | 27 | 380 |
| ('5c', 'child', 'train') | 10 | 780 |
| ('5c', 'child', 'validation') | 11 | 878 |
| ('5c', 'child_prototypical', 'train') | 39 | 506 |
| ('5c', 'child_prototypical', 'validation') | 45 | 605 |
| ('5d', 'child', 'train') | 10 | 780 |
| ('5d', 'child', 'validation') | 15 | 874 |
| ('5d', 'child_prototypical', 'train') | 39 | 428 |
| ('5d', 'child_prototypical', 'validation') | 69 | 923 |
| ('5e', 'child', 'train') | 10 | 780 |
| ('5e', 'child', 'validation') | 8 | 881 |
| ('5e', 'child_prototypical', 'train') | 39 | 584 |
| ('5e', 'child_prototypical', 'validation') | 27 | 380 |
| ('5f', 'child', 'train') | 10 | 780 |
| ('5f', 'child', 'validation') | 11 | 878 |
| ('5f', 'child_prototypical', 'train') | 39 | 584 |
| ('5f', 'child_prototypical', 'validation') | 45 | 695 |
| ('5g', 'child', 'train') | 10 | 780 |
| ('5g', 'child', 'validation') | 9 | 880 |
| ('5g', 'child_prototypical', 'train') | 39 | 623 |
| ('5g', 'child_prototypical', 'validation') | 33 | 512 |
| ('5h', 'child', 'train') | 10 | 780 |
| ('5h', 'child', 'validation') | 15 | 874 |
| ('5h', 'child_prototypical', 'train') | 39 | 545 |
| ('5h', 'child_prototypical', 'validation') | 69 | 1130 |
| ('5i', 'child', 'train') | 10 | 780 |
| ('5i', 'child', 'validation') | 14 | 875 |
| ('5i', 'child_prototypical', 'train') | 39 | 545 |
| ('5i', 'child_prototypical', 'validation') | 63 | 1001 |
| ('6', 'parent', 'train') | 80 | 710 |
| ('6', 'parent', 'validation') | 99 | 790 |
| ('6a', 'child', 'train') | 10 | 780 |
| ('6a', 'child', 'validation') | 15 | 874 |
| ('6a', 'child_prototypical', 'train') | 39 | 467 |
| ('6a', 'child_prototypical', 'validation') | 69 | 992 |
| ('6b', 'child', 'train') | 10 | 780 |
| ('6b', 'child', 'validation') | 11 | 878 |
| ('6b', 'child_prototypical', 'train') | 39 | 584 |
| ('6b', 'child_prototypical', 'validation') | 45 | 695 |
| ('6c', 'child', 'train') | 10 | 780 |
| ('6c', 'child', 'validation') | 13 | 876 |
| ('6c', 'child_prototypical', 'train') | 39 | 584 |
| ('6c', 'child_prototypical', 'validation') | 57 | 935 |
| ('6d', 'child', 'train') | 10 | 780 |
| ('6d', 'child', 'validation') | 10 | 879 |
| ('6d', 'child_prototypical', 'train') | 39 | 701 |
| ('6d', 'child_prototypical', 'validation') | 39 | 701 |
| ('6e', 'child', 'train') | 10 | 780 |
| ('6e', 'child', 'validation') | 11 | 878 |
| ('6e', 'child_prototypical', 'train') | 39 | 584 |
| ('6e', 'child_prototypical', 'validation') | 45 | 695 |
| ('6f', 'child', 'train') | 10 | 780 |
| ('6f', 'child', 'validation') | 12 | 877 |
| ('6f', 'child_prototypical', 'train') | 39 | 506 |
| ('6f', 'child_prototypical', 'validation') | 51 | 710 |
| ('6g', 'child', 'train') | 10 | 780 |
| ('6g', 'child', 'validation') | 12 | 877 |
| ('6g', 'child_prototypical', 'train') | 39 | 467 |
| ('6g', 'child_prototypical', 'validation') | 51 | 659 |
| ('6h', 'child', 'train') | 10 | 780 |
| ('6h', 'child', 'validation') | 15 | 874 |
| ('6h', 'child_prototypical', 'train') | 39 | 506 |
| ('6h', 'child_prototypical', 'validation') | 69 | 1061 |
| ('7', 'parent', 'train') | 80 | 710 |
| ('7', 'parent', 'validation') | 91 | 798 |
| ('7a', 'child', 'train') | 10 | 780 |
| ('7a', 'child', 'validation') | 14 | 875 |
| ('7a', 'child_prototypical', 'train') | 39 | 545 |
| ('7a', 'child_prototypical', 'validation') | 63 | 1001 |
| ('7b', 'child', 'train') | 10 | 780 |
| ('7b', 'child', 'validation') | 7 | 882 |
| ('7b', 'child_prototypical', 'train') | 39 | 389 |
| ('7b', 'child_prototypical', 'validation') | 21 | 182 |
| ('7c', 'child', 'train') | 10 | 780 |
| ('7c', 'child', 'validation') | 11 | 878 |
| ('7c', 'child_prototypical', 'train') | 39 | 428 |
| ('7c', 'child_prototypical', 'validation') | 45 | 515 |
| ('7d', 'child', 'train') | 10 | 780 |
| ('7d', 'child', 'validation') | 14 | 875 |
| ('7d', 'child_prototypical', 'train') | 39 | 545 |
| ('7d', 'child_prototypical', 'validation') | 63 | 1001 |
| ('7e', 'child', 'train') | 10 | 780 |
| ('7e', 'child', 'validation') | 10 | 879 |
| ('7e', 'child_prototypical', 'train') | 39 | 428 |
| ('7e', 'child_prototypical', 'validation') | 39 | 428 |
| ('7f', 'child', 'train') | 10 | 780 |
| ('7f', 'child', 'validation') | 12 | 877 |
| ('7f', 'child_prototypical', 'train') | 39 | 389 |
| ('7f', 'child_prototypical', 'validation') | 51 | 557 |
| ('7g', 'child', 'train') | 10 | 780 |
| ('7g', 'child', 'validation') | 9 | 880 |
| ('7g', 'child_prototypical', 'train') | 39 | 311 |
| ('7g', 'child_prototypical', 'validation') | 33 | 248 |
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| ('7h', 'child', 'validation') | 14 | 875 |
| ('7h', 'child_prototypical', 'train') | 39 | 350 |
| ('7h', 'child_prototypical', 'validation') | 63 | 686 |
| ('8', 'parent', 'train') | 80 | 710 |
| ('8', 'parent', 'validation') | 90 | 799 |
| ('8a', 'child', 'train') | 10 | 780 |
| ('8a', 'child', 'validation') | 14 | 875 |
| ('8a', 'child_prototypical', 'train') | 39 | 428 |
| ('8a', 'child_prototypical', 'validation') | 63 | 812 |
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| ('8b', 'child', 'validation') | 7 | 882 |
| ('8b', 'child_prototypical', 'train') | 39 | 584 |
| ('8b', 'child_prototypical', 'validation') | 21 | 287 |
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| ('8c', 'child', 'validation') | 12 | 877 |
| ('8c', 'child_prototypical', 'train') | 39 | 389 |
| ('8c', 'child_prototypical', 'validation') | 51 | 557 |
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| ('8d', 'child', 'validation') | 13 | 876 |
| ('8d', 'child_prototypical', 'train') | 39 | 389 |
| ('8d', 'child_prototypical', 'validation') | 57 | 650 |
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| ('8e', 'child', 'validation') | 11 | 878 |
| ('8e', 'child_prototypical', 'train') | 39 | 389 |
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| ('8f', 'child', 'validation') | 12 | 877 |
| ('8f', 'child_prototypical', 'train') | 39 | 428 |
| ('8f', 'child_prototypical', 'validation') | 51 | 608 |
| ('8g', 'child', 'train') | 10 | 780 |
| ('8g', 'child', 'validation') | 7 | 882 |
| ('8g', 'child_prototypical', 'train') | 39 | 272 |
| ('8g', 'child_prototypical', 'validation') | 21 | 119 |
| ('8h', 'child', 'train') | 10 | 780 |
| ('8h', 'child', 'validation') | 14 | 875 |
| ('8h', 'child_prototypical', 'train') | 39 | 467 |
| ('8h', 'child_prototypical', 'validation') | 63 | 875 |
| ('9', 'parent', 'train') | 90 | 700 |
| ('9', 'parent', 'validation') | 96 | 793 |
| ('9a', 'child', 'train') | 10 | 780 |
| ('9a', 'child', 'validation') | 14 | 875 |
| ('9a', 'child_prototypical', 'train') | 39 | 350 |
| ('9a', 'child_prototypical', 'validation') | 63 | 686 |
| ('9b', 'child', 'train') | 10 | 780 |
| ('9b', 'child', 'validation') | 12 | 877 |
| ('9b', 'child_prototypical', 'train') | 39 | 506 |
| ('9b', 'child_prototypical', 'validation') | 51 | 710 |
| ('9c', 'child', 'train') | 10 | 780 |
| ('9c', 'child', 'validation') | 7 | 882 |
| ('9c', 'child_prototypical', 'train') | 39 | 155 |
| ('9c', 'child_prototypical', 'validation') | 21 | 56 |
| ('9d', 'child', 'train') | 10 | 780 |
| ('9d', 'child', 'validation') | 9 | 880 |
| ('9d', 'child_prototypical', 'train') | 39 | 662 |
| ('9d', 'child_prototypical', 'validation') | 33 | 545 |
| ('9e', 'child', 'train') | 10 | 780 |
| ('9e', 'child', 'validation') | 8 | 881 |
| ('9e', 'child_prototypical', 'train') | 39 | 701 |
| ('9e', 'child_prototypical', 'validation') | 27 | 461 |
| ('9f', 'child', 'train') | 10 | 780 |
| ('9f', 'child', 'validation') | 10 | 879 |
| ('9f', 'child_prototypical', 'train') | 39 | 506 |
| ('9f', 'child_prototypical', 'validation') | 39 | 506 |
| ('9g', 'child', 'train') | 10 | 780 |
| ('9g', 'child', 'validation') | 14 | 875 |
| ('9g', 'child_prototypical', 'train') | 39 | 389 |
| ('9g', 'child_prototypical', 'validation') | 63 | 749 |
| ('9h', 'child', 'train') | 10 | 780 |
| ('9h', 'child', 'validation') | 13 | 876 |
| ('9h', 'child_prototypical', 'train') | 39 | 506 |
| ('9h', 'child_prototypical', 'validation') | 57 | 821 |
| ('9i', 'child', 'train') | 10 | 780 |
| ('9i', 'child', 'validation') | 9 | 880 |
| ('9i', 'child_prototypical', 'train') | 39 | 506 |
| ('9i', 'child_prototypical', 'validation') | 33 | 413 |
### Citation Information
```
@inproceedings{jurgens-etal-2012-semeval,
title = "{S}em{E}val-2012 Task 2: Measuring Degrees of Relational Similarity",
author = "Jurgens, David and
Mohammad, Saif and
Turney, Peter and
Holyoak, Keith",
booktitle = "*{SEM} 2012: The First Joint Conference on Lexical and Computational Semantics {--} Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation ({S}em{E}val 2012)",
month = "7-8 " # jun,
year = "2012",
address = "Montr{\'e}al, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/S12-1047",
pages = "356--364",
}
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0.774603009223938,
0.2563217282295227,
-0.7852813005447388,
-0.22573819756507874,
-0.9104477167129517,
0.5715674161911011,
-... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
Nerfgun3/flower_style | Nerfgun3 | 2022-11-17T13:54:16Z | 15 | 10 | null | [
"language:en",
"license:creativeml-openrail-m",
"stable-diffusion",
"text-to-image",
"image-to-image",
"region:us"
] | 2022-11-17T13:54:16Z | 2022-10-23T20:34:36.000Z | 2022-10-23T20:34:36 | ---
language:
- en
license: creativeml-openrail-m
thumbnail: "https://huggingface.co/datasets/Nerfgun3/flower_style/resolve/main/flower_style_showcase.jpg"
tags:
- stable-diffusion
- text-to-image
- image-to-image
inference: false
---
# Flower Style Embedding / Textual Inversion
<img alt="Showcase" src="https://huggingface.co/datasets/Nerfgun3/flower_style/resolve/main/flower_style_showcase.jpg"/>
## Usage
To use this embedding you have to download the file aswell as drop it into the "\stable-diffusion-webui\embeddings" folder
To use it in a prompt: ```"art by flower_style"```
If it is to strong just add [] around it.
Trained until 15000 steps
I added a 7.5k steps trained ver in the files aswell. If you want to use that version, remove the ```"-7500"``` from the file name and replace the 15k steps ver in your folder
Have fun :)
## License
This embedding is open access and available to all, with a CreativeML OpenRAIL-M license further specifying rights and usage.
The CreativeML OpenRAIL License specifies:
1. You can't use the embedding to deliberately produce nor share illegal or harmful outputs or content
2. The authors claims no rights on the outputs you generate, you are free to use them and are accountable for their use which must not go against the provisions set in the license
3. You may re-distribute the weights and use the embedding commercially and/or as a service. If you do, please be aware you have to include the same use restrictions as the ones in the license and share a copy of the CreativeML OpenRAIL-M to all your users (please read the license entirely and carefully)
[Please read the full license here](https://huggingface.co/spaces/CompVis/stable-diffusion-license) | [
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autoevaluate/autoeval-eval-jeffdshen__neqa0_8shot-jeffdshen__neqa0_8shot-5a61bc-1852963391 | autoevaluate | 2022-10-23T21:04:17Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-10-23T21:04:17Z | 2022-10-23T20:59:43.000Z | 2022-10-23T20:59:43 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- jeffdshen/neqa0_8shot
eval_info:
task: text_zero_shot_classification
model: inverse-scaling/opt-125m_eval
metrics: []
dataset_name: jeffdshen/neqa0_8shot
dataset_config: jeffdshen--neqa0_8shot
dataset_split: train
col_mapping:
text: prompt
classes: classes
target: answer_index
---
# 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: inverse-scaling/opt-125m_eval
* Dataset: jeffdshen/neqa0_8shot
* Config: jeffdshen--neqa0_8shot
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@jeffdshen](https://huggingface.co/jeffdshen) for evaluating this model. | [
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0.021699333... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
autoevaluate/autoeval-eval-jeffdshen__neqa0_8shot-jeffdshen__neqa0_8shot-5a61bc-1852963392 | autoevaluate | 2022-10-23T21:07:19Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-10-23T21:07:19Z | 2022-10-23T20:59:43.000Z | 2022-10-23T20:59:43 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- jeffdshen/neqa0_8shot
eval_info:
task: text_zero_shot_classification
model: inverse-scaling/opt-350m_eval
metrics: []
dataset_name: jeffdshen/neqa0_8shot
dataset_config: jeffdshen--neqa0_8shot
dataset_split: train
col_mapping:
text: prompt
classes: classes
target: answer_index
---
# 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: inverse-scaling/opt-350m_eval
* Dataset: jeffdshen/neqa0_8shot
* Config: jeffdshen--neqa0_8shot
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@jeffdshen](https://huggingface.co/jeffdshen) for evaluating this model. | [
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0.01696357876... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
autoevaluate/autoeval-eval-jeffdshen__neqa0_8shot-jeffdshen__neqa0_8shot-5a61bc-1852963394 | autoevaluate | 2022-10-23T21:31:31Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-10-23T21:31:31Z | 2022-10-23T20:59:43.000Z | 2022-10-23T20:59:43 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- jeffdshen/neqa0_8shot
eval_info:
task: text_zero_shot_classification
model: inverse-scaling/opt-2.7b_eval
metrics: []
dataset_name: jeffdshen/neqa0_8shot
dataset_config: jeffdshen--neqa0_8shot
dataset_split: train
col_mapping:
text: prompt
classes: classes
target: answer_index
---
# 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: inverse-scaling/opt-2.7b_eval
* Dataset: jeffdshen/neqa0_8shot
* Config: jeffdshen--neqa0_8shot
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@jeffdshen](https://huggingface.co/jeffdshen) for evaluating this model. | [
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-0.00128921424... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
autoevaluate/autoeval-eval-jeffdshen__neqa2_8shot-jeffdshen__neqa2_8shot-959823-1853063399 | autoevaluate | 2022-10-23T21:02:53Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-10-23T21:02:53Z | 2022-10-23T20:59:46.000Z | 2022-10-23T20:59:46 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- jeffdshen/neqa2_8shot
eval_info:
task: text_zero_shot_classification
model: inverse-scaling/opt-125m_eval
metrics: []
dataset_name: jeffdshen/neqa2_8shot
dataset_config: jeffdshen--neqa2_8shot
dataset_split: train
col_mapping:
text: prompt
classes: classes
target: answer_index
---
# 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: inverse-scaling/opt-125m_eval
* Dataset: jeffdshen/neqa2_8shot
* Config: jeffdshen--neqa2_8shot
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@jeffdshen](https://huggingface.co/jeffdshen) for evaluating this model. | [
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0.00319181... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
autoevaluate/autoeval-eval-jeffdshen__neqa2_8shot-jeffdshen__neqa2_8shot-959823-1853063406 | autoevaluate | 2022-10-24T04:31:40Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-10-24T04:31:40Z | 2022-10-23T21:09:53.000Z | 2022-10-23T21:09:53 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- jeffdshen/neqa2_8shot
eval_info:
task: text_zero_shot_classification
model: inverse-scaling/opt-66b_eval
metrics: []
dataset_name: jeffdshen/neqa2_8shot
dataset_config: jeffdshen--neqa2_8shot
dataset_split: train
col_mapping:
text: prompt
classes: classes
target: answer_index
---
# 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: inverse-scaling/opt-66b_eval
* Dataset: jeffdshen/neqa2_8shot
* Config: jeffdshen--neqa2_8shot
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@jeffdshen](https://huggingface.co/jeffdshen) for evaluating this model. | [
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0.01387867704... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
autoevaluate/autoeval-eval-jeffdshen__redefine_math2_8shot-jeffdshen__redefine_mat-af4c71-1853163407 | autoevaluate | 2022-10-23T21:13:41Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-10-23T21:13:41Z | 2022-10-23T21:10:08.000Z | 2022-10-23T21:10:08 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- jeffdshen/redefine_math2_8shot
eval_info:
task: text_zero_shot_classification
model: inverse-scaling/opt-125m_eval
metrics: []
dataset_name: jeffdshen/redefine_math2_8shot
dataset_config: jeffdshen--redefine_math2_8shot
dataset_split: train
col_mapping:
text: prompt
classes: classes
target: answer_index
---
# 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: inverse-scaling/opt-125m_eval
* Dataset: jeffdshen/redefine_math2_8shot
* Config: jeffdshen--redefine_math2_8shot
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@jeffdshen](https://huggingface.co/jeffdshen) for evaluating this model. | [
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autoevaluate/autoeval-eval-jeffdshen__redefine_math0_8shot-jeffdshen__redefine_mat-1c694b-1853263417 | autoevaluate | 2022-10-23T21:55:09Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-10-23T21:55:09Z | 2022-10-23T21:39:03.000Z | 2022-10-23T21:39:03 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- jeffdshen/redefine_math0_8shot
eval_info:
task: text_zero_shot_classification
model: inverse-scaling/opt-1.3b_eval
metrics: []
dataset_name: jeffdshen/redefine_math0_8shot
dataset_config: jeffdshen--redefine_math0_8shot
dataset_split: train
col_mapping:
text: prompt
classes: classes
target: answer_index
---
# 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: inverse-scaling/opt-1.3b_eval
* Dataset: jeffdshen/redefine_math0_8shot
* Config: jeffdshen--redefine_math0_8shot
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@jeffdshen](https://huggingface.co/jeffdshen) for evaluating this model. | [
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autoevaluate/autoeval-eval-jeffdshen__redefine_math0_8shot-jeffdshen__redefine_mat-1c694b-1853263422 | autoevaluate | 2022-10-24T06:32:10Z | 15 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-10-24T06:32:10Z | 2022-10-23T22:01:16.000Z | 2022-10-23T22:01:16 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- jeffdshen/redefine_math0_8shot
eval_info:
task: text_zero_shot_classification
model: inverse-scaling/opt-66b_eval
metrics: []
dataset_name: jeffdshen/redefine_math0_8shot
dataset_config: jeffdshen--redefine_math0_8shot
dataset_split: train
col_mapping:
text: prompt
classes: classes
target: answer_index
---
# 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: inverse-scaling/opt-66b_eval
* Dataset: jeffdshen/redefine_math0_8shot
* Config: jeffdshen--redefine_math0_8shot
* Split: train
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@jeffdshen](https://huggingface.co/jeffdshen) for evaluating this model. | [
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salascorp/34 | salascorp | 2022-10-23T23:18:45Z | 15 | 0 | null | [
"region:us"
] | 2022-10-23T23:18:45Z | 2022-10-23T23:16:50.000Z | 2022-10-23T23:16:50 | Entry not found | [
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-0... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
JesusMaginge/modelo.de.entrenamiento | JesusMaginge | 2022-10-24T02:04:28Z | 15 | 0 | null | [
"license:openrail",
"region:us"
] | 2022-10-24T02:04:28Z | 2022-10-24T02:01:45.000Z | 2022-10-24T02:01:45 | ---
license: openrail
---
| [
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ionghin/digimon-blip-captions | ionghin | 2022-10-24T02:31:17Z | 15 | 1 | null | [
"license:cc-by-nc-sa-4.0",
"region:us"
] | 2022-10-24T02:31:17Z | 2022-10-24T02:31:05.000Z | 2022-10-24T02:31:05 | ---
license: cc-by-nc-sa-4.0
---
| [
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UriD7/Oriol_Training | UriD7 | 2022-10-24T11:00:53Z | 15 | 0 | null | [
"region:us"
] | 2022-10-24T11:00:53Z | 2022-10-24T10:57:59.000Z | 2022-10-24T10:57:59 | Entry not found | [
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wjchenCUC/tutu_dog | wjchenCUC | 2022-10-24T11:25:37Z | 15 | 0 | null | [
"region:us"
] | 2022-10-24T11:25:37Z | 2022-10-24T11:18:01.000Z | 2022-10-24T11:18:01 | Entry not found | [
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LHF/l3d | LHF | 2023-01-02T19:41:27Z | 15 | 0 | null | [
"region:us"
] | 2023-01-02T19:41:27Z | 2022-10-24T15:31:20.000Z | 2022-10-24T15:31:20 | # Large Labelled Logo Dataset | [
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... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
arbml/Shami | arbml | 2022-10-24T16:09:29Z | 15 | 0 | null | [
"region:us"
] | 2022-10-24T16:09:29Z | 2022-10-24T16:09:15.000Z | 2022-10-24T16:09:15 | Entry not found | [
-0.32276472449302673,
-0.22568407654762268,
0.8622258901596069,
0.4346148371696472,
-0.5282984972000122,
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-0.9104482531547546,
0.5715669393539429,
... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
andrewkroening/Star-wars-scripts-dialogue-IV-VI | andrewkroening | 2022-10-27T17:53:39Z | 15 | 1 | null | [
"license:cc",
"region:us"
] | 2022-10-27T17:53:39Z | 2022-10-24T19:31:55.000Z | 2022-10-24T19:31:55 | ---
license: cc
---
### Dataset Contents
This dataset contains the concatenated scripts from the original (and best) Star Wars trilogy. The scripts are reduced to dialogue only, and are tagged with a line number and speaker.
### Dataset Disclaimer
I don't own this data; or Star Wars. But it would be cool if I did.
Star Wars is owned by Lucasfilms. I do not own any of the rights to this information.
The scripts are derived from a couple sources:
* This [GitHub Repo](https://github.com/gastonstat/StarWars) with raw files
* A [Kaggle Dataset](https://www.kaggle.com/datasets/xvivancos/star-wars-movie-scripts) put together by whoever 'Xavier' is
### May the Force be with you | [
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0.2470069974... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
arias048/myPictures | arias048 | 2022-10-28T19:45:30Z | 15 | 0 | null | [
"license:other",
"region:us"
] | 2022-10-28T19:45:30Z | 2022-10-25T14:01:11.000Z | 2022-10-25T14:01:11 | ---
license: other
---
| [
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-0.0478260256350... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
tomekkorbak/codeparrot-pep8-scored | tomekkorbak | 2022-10-25T20:14:40Z | 15 | 0 | null | [
"region:us"
] | 2022-10-25T20:14:40Z | 2022-10-25T20:12:34.000Z | 2022-10-25T20:12:34 | ---
dataset_info:
features:
- name: repo_name
dtype: string
- name: path
dtype: string
- name: copies
dtype: string
- name: size
dtype: string
- name: content
dtype: string
- name: license
dtype: string
- name: hash
dtype: int64
- name: line_mean
dtype: float64
- name: line_max
dtype: int64
- name: alpha_frac
dtype: float64
- name: autogenerated
dtype: bool
- name: ratio
dtype: float64
- name: config_test
dtype: bool
- name: has_no_keywords
dtype: bool
- name: few_assignments
dtype: bool
- name: score
dtype: float64
splits:
- name: test
num_bytes: 1556261021.25
num_examples: 150000
- name: train
num_bytes: 518753673.75
num_examples: 50000
download_size: 771399764
dataset_size: 2075014695.0
---
# Dataset Card for "codeparrot-pep8-scored"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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-0.077220521... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
lipaoMai/github-issues | lipaoMai | 2022-10-25T20:17:38Z | 15 | 0 | null | [
"region:us"
] | 2022-10-25T20:17:38Z | 2022-10-25T20:17:29.000Z | 2022-10-25T20:17:29 | ---
dataset_info:
features:
- name: patient_id
dtype: int64
- name: drugName
dtype: string
- name: condition
dtype: string
- name: review
dtype: string
- name: rating
dtype: float64
- name: date
dtype: string
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dtype: int64
splits:
- name: test
num_bytes: 28367208
num_examples: 53471
- name: train
num_bytes: 85172055
num_examples: 160398
download_size: 63481104
dataset_size: 113539263
---
# Dataset Card for "github-issues"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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olm/olm-CC-MAIN-2017-22-sampling-ratio-0.16178770949 | olm | 2022-11-04T17:12:48Z | 15 | 0 | null | [
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10M<n<100M",
"language:en",
"pretraining",
"language modelling",
"common crawl",
"web",
"region:us"
] | 2022-11-04T17:12:48Z | 2022-10-25T22:33:21.000Z | 2022-10-25T22:33:21 | ---
annotations_creators:
- no-annotation
language:
- en
language_creators:
- found
license: []
multilinguality:
- monolingual
pretty_name: OLM May 2017 Common Crawl
size_categories:
- 10M<n<100M
source_datasets: []
tags:
- pretraining
- language modelling
- common crawl
- web
task_categories: []
task_ids: []
---
# Dataset Card for OLM May 2017 Common Crawl
Cleaned and deduplicated pretraining dataset, created with the OLM repo [here](https://github.com/huggingface/olm-datasets) from 16% of the May 2017 Common Crawl snapshot.
Note: `last_modified_timestamp` was parsed from whatever a website returned in it's `Last-Modified` header; there are likely a small number of outliers that are incorrect, so we recommend removing the outliers before doing statistics with `last_modified_timestamp`. | [
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-0.01187165081501... | null | null | null | null | null | null | null | null | null | null | null | null | null |
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