id stringlengths 2 115 | author stringlengths 2 42 ⌀ | last_modified timestamp[us, tz=UTC] | downloads int64 0 8.87M | likes int64 0 3.84k | paperswithcode_id stringlengths 2 45 ⌀ | tags list | lastModified timestamp[us, tz=UTC] | createdAt stringlengths 24 24 | key stringclasses 1 value | created timestamp[us] | card stringlengths 1 1.01M | embedding list | library_name stringclasses 21 values | pipeline_tag stringclasses 27 values | mask_token null | card_data null | widget_data null | model_index null | config null | transformers_info null | spaces null | safetensors null | transformersInfo null | modelId stringlengths 5 111 ⌀ | embeddings list |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
KETI-AIR/aihub_dialog_summarization | KETI-AIR | 2022-10-31T06:10:39Z | 12 | 1 | null | [
"license:apache-2.0",
"region:us"
] | 2022-10-31T06:10:39Z | 2022-10-28T11:40:25.000Z | 2022-10-28T11:40:25 | ---
license: apache-2.0
---
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tglcourse/latent_celebA_256px | tglcourse | 2022-10-28T11:49:27Z | 12 | 0 | null | [
"region:us"
] | 2022-10-28T11:49:27Z | 2022-10-28T11:45:46.000Z | 2022-10-28T11:45:46 | ---
dataset_info:
features:
- name: latent
sequence:
sequence:
sequence: float32
splits:
- name: train
num_bytes: 3427164684
num_examples: 202599
download_size: 3338993120
dataset_size: 3427164684
---
# Dataset Card for "latent_celebA_256px"
Each image is cropped to 256px square and encoded to a 4x32x32 latent representation using the same VAE as that employed by Stable Diffusion
Decoding
```python
from diffusers import AutoencoderKL
from datasets import load_dataset
from PIL import Image
import numpy as np
import torch
# load the dataset
dataset = load_dataset('tglcourse/latent_celebA_256px')
# Load the VAE (requires access - see repo model card for info)
vae = AutoencoderKL.from_pretrained("CompVis/stable-diffusion-v1-4", subfolder="vae")
latent = torch.tensor([dataset['train'][0]['latent']]) # To tensor (bs, 4, 32, 32)
latent = (1 / 0.18215) * latent # Scale to match SD implementation
with torch.no_grad():
image = vae.decode(latent).sample[0] # Decode
image = (image / 2 + 0.5).clamp(0, 1) # To (0, 1)
image = image.detach().cpu().permute(1, 2, 0).numpy() # To numpy, channels lsat
image = (image * 255).round().astype("uint8") # (0, 255) and type uint8
image = Image.fromarray(image) # To PIL
image # The resulting PIL image
``` | [
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efederici/mt_nap_it | efederici | 2022-10-28T14:32:26Z | 12 | 1 | null | [
"task_categories:translation",
"size_categories:unknown",
"language:it",
"license:unknown",
"conditional-text-generation",
"region:us"
] | 2022-10-28T14:32:26Z | 2022-10-28T11:51:09.000Z | 2022-10-28T11:51:09 | ---
language:
- it
license:
- unknown
size_categories:
- unknown
task_categories:
- translation
task_ids: []
pretty_name: mt_nap_it
tags:
- conditional-text-generation
---
# Dataset Card for mt_en_it
## Table of Contents
- [Dataset Card for mt_en_it](#dataset-card-for-mt-en-it)
- [Table of Contents](#table-of-contents)
- [Dataset Summary](#dataset-summary)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Dataset Creation](#dataset-creation)
### Dataset Summary
This dataset comprises traditional Neapolitan songs from [napoligrafia](https://www.napoligrafia.it) translated into Italian.
### Languages
- italian-to-neapolitan
### Data Instances
A sample from the dataset.
```python
{
'url': "url",
'napoletano': "o, quacche ghiuorno, 'a frennesia mme piglia",
'italiano': "o, qualche giorno, la rabbia mi prende"
}
```
The text is provided without further preprocessing or tokenization.
### Data Fields
- `url`: source URL.
- `napoletano`: Neapolitan text.
- `italiano`: Italian text.
### Dataset Creation
The dataset was created by scraping [napoligrafia](https://www.napoligrafia.it) songs. | [
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arbml/kawarith_Covid_19 | arbml | 2022-10-28T13:20:05Z | 12 | 0 | null | [
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arbml/kawarith_Dragon_storms | arbml | 2022-10-28T13:21:08Z | 12 | 0 | null | [
"region:us"
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arbml/kawarith_Hafr_floods | arbml | 2022-10-28T13:23:33Z | 12 | 0 | null | [
"region:us"
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maximedb/massive_generated | maximedb | 2022-10-28T13:43:16Z | 12 | 0 | null | [
"license:mit",
"region:us"
] | 2022-10-28T13:43:16Z | 2022-10-28T13:42:35.000Z | 2022-10-28T13:42:35 | ---
license: mit
---
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arbml/SemEval_2017_ar_subtask_A | arbml | 2022-10-28T13:46:31Z | 12 | 0 | null | [
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arbml/ArCOV19_claims | arbml | 2022-10-28T13:56:50Z | 12 | 0 | null | [
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autoevaluate/autoeval-eval-mathemakitten__winobias_antistereotype_test_cot_v1-math-1bbcaf-1917164990 | autoevaluate | 2022-10-28T14:26:30Z | 12 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-10-28T14:26:30Z | 2022-10-28T14:22:43.000Z | 2022-10-28T14:22:43 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- mathemakitten/winobias_antistereotype_test_cot_v1
eval_info:
task: text_zero_shot_classification
model: inverse-scaling/opt-1.3b_eval
metrics: []
dataset_name: mathemakitten/winobias_antistereotype_test_cot_v1
dataset_config: mathemakitten--winobias_antistereotype_test_cot_v1
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: inverse-scaling/opt-1.3b_eval
* Dataset: mathemakitten/winobias_antistereotype_test_cot_v1
* Config: mathemakitten--winobias_antistereotype_test_cot_v1
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@mathemakitten](https://huggingface.co/mathemakitten) for evaluating this model. | [
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autoevaluate/autoeval-eval-mathemakitten__winobias_antistereotype_test_cot_v1-math-1bbcaf-1917164991 | autoevaluate | 2022-10-28T14:28:19Z | 12 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-10-28T14:28:19Z | 2022-10-28T14:22:44.000Z | 2022-10-28T14:22:44 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- mathemakitten/winobias_antistereotype_test_cot_v1
eval_info:
task: text_zero_shot_classification
model: inverse-scaling/opt-2.7b_eval
metrics: []
dataset_name: mathemakitten/winobias_antistereotype_test_cot_v1
dataset_config: mathemakitten--winobias_antistereotype_test_cot_v1
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: inverse-scaling/opt-2.7b_eval
* Dataset: mathemakitten/winobias_antistereotype_test_cot_v1
* Config: mathemakitten--winobias_antistereotype_test_cot_v1
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@mathemakitten](https://huggingface.co/mathemakitten) for evaluating this model. | [
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autoevaluate/autoeval-eval-mathemakitten__winobias_antistereotype_test_cot_v1-math-1bbcaf-1917164992 | autoevaluate | 2022-10-28T14:50:20Z | 12 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-10-28T14:50:20Z | 2022-10-28T14:22:46.000Z | 2022-10-28T14:22:46 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- mathemakitten/winobias_antistereotype_test_cot_v1
eval_info:
task: text_zero_shot_classification
model: inverse-scaling/opt-13b_eval
metrics: []
dataset_name: mathemakitten/winobias_antistereotype_test_cot_v1
dataset_config: mathemakitten--winobias_antistereotype_test_cot_v1
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: inverse-scaling/opt-13b_eval
* Dataset: mathemakitten/winobias_antistereotype_test_cot_v1
* Config: mathemakitten--winobias_antistereotype_test_cot_v1
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@mathemakitten](https://huggingface.co/mathemakitten) for evaluating this model. | [
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DJSoft/maccha_artist_style | DJSoft | 2022-11-27T16:00:22Z | 12 | 0 | null | [
"license:creativeml-openrail-m",
"region:us"
] | 2022-11-27T16:00:22Z | 2022-10-28T15:06:19.000Z | 2022-10-28T15:06:19 | ---
license: creativeml-openrail-m
---
# Maccha style embedding
## Samples
<img alt="Samples" src="https://huggingface.co/datasets/DJSoft/maccha_artist_style/resolve/main/samples.jpg" style="max-height: 80vh"/>
<img alt="Comparsion" src="https://huggingface.co/datasets/DJSoft/maccha_artist_style/resolve/main/steps.png" style="max-height: 80vh"/>
## About
Use this Stable Diffusion embedding to achieve style of Matcha_ / maccha_(mochancc) [Pixiv](https://www.pixiv.net/en/users/2583663)
## Usage
To use this embedding you have to download the file and put it into the "\stable-diffusion-webui\embeddings" folder
To use it in a prompt add __art by maccha-*__
Add **( :1.0)** around it to modify its weight
## Included Files
- 8000 steps Usage: **art by maccha-8000**
- 15000 steps Usage: **art by maccha-15000**
## 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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DJSoft/yuki_miku_2017_outfit | DJSoft | 2022-11-27T15:43:43Z | 12 | 0 | null | [
"license:creativeml-openrail-m",
"region:us"
] | 2022-11-27T15:43:43Z | 2022-10-28T15:43:14.000Z | 2022-10-28T15:43:14 | ---
license: creativeml-openrail-m
---
# Yuki Miku 2017 embedding
## Samples
<img alt="Samples" src="https://huggingface.co/datasets/DJSoft/yuki_miku_2017_outfit/resolve/main/samples.jpg" style="max-height: 80vh"/>
<img alt="Comparsion" src="https://huggingface.co/datasets/DJSoft/yuki_miku_2017_outfit/resolve/main/steps.png" style="max-height: 80vh"/>
## About
Use this Stable Diffusion embedding to achieve the Hatsune Miku Yuki Style 2017 outfit
## Usage
To use this embedding you have to download the file and put it into the "\stable-diffusion-webui\embeddings" folder
To use it in a prompt add __yuki_miku_2017-*__
Add **( :1.0)** around it to modify its weight
## Included Files
- 8000 steps Usage: **yuki_miku_2017-8000**
- 10000 steps Usage: **yuki_miku_2017-10000**
- 15000 steps Usage: **yuki_miku_2017-15000**
## 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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nixjoe/mylover1 | nixjoe | 2022-10-28T15:58:32Z | 12 | 0 | null | [
"license:unknown",
"region:us"
] | 2022-10-28T15:58:32Z | 2022-10-28T15:57:33.000Z | 2022-10-28T15:57:33 | ---
license: unknown
---
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Toveline/images | Toveline | 2022-10-28T19:08:39Z | 12 | 0 | null | [
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license: unknown
---
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kanak8278/focus_test | kanak8278 | 2022-10-28T18:42:53Z | 12 | 0 | null | [
"region:us"
] | 2022-10-28T18:42:53Z | 2022-10-28T18:42:49.000Z | 2022-10-28T18:42:49 | ---
dataset_info:
features:
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splits:
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download_size: 2783764
dataset_size: 6713468
---
# Dataset Card for "focus_test"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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MarkGG/Romance-cleaned-3 | MarkGG | 2022-10-29T06:03:39Z | 12 | 0 | null | [
"region:us"
] | 2022-10-29T06:03:39Z | 2022-10-29T06:03:19.000Z | 2022-10-29T06:03:19 | ---
dataset_info:
features:
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splits:
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num_bytes: 374729.4907446068
num_examples: 719
download_size: 2300275
dataset_size: 3744689.0
---
# Dataset Card for "Romance-cleaned-3"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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Toveline/toveline | Toveline | 2022-10-30T11:35:14Z | 12 | 0 | null | [
"license:unknown",
"region:us"
] | 2022-10-30T11:35:14Z | 2022-10-29T12:12:03.000Z | 2022-10-29T12:12:03 | ---
license: unknown
---
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Dialogue-Model-Research-Group/baike | Dialogue-Model-Research-Group | 2022-11-12T16:00:22Z | 12 | 1 | null | [
"license:cc",
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license: cc
---
| [
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autoevaluate/autoeval-eval-cnn_dailymail-3.0.0-98a820-1924665124 | autoevaluate | 2022-10-29T15:11:10Z | 12 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-10-29T15:11:10Z | 2022-10-29T14:24:53.000Z | 2022-10-29T14:24:53 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- cnn_dailymail
eval_info:
task: summarization
model: patrickvonplaten/bert2bert_cnn_daily_mail
metrics: ['accuracy', '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: patrickvonplaten/bert2bert_cnn_daily_mail
* 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 [@Jomon07](https://huggingface.co/Jomon07) for evaluating this model. | [
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ghomasHudson/muld_AO3_Style_Change_Detection | ghomasHudson | 2022-11-02T12:06:59Z | 12 | 0 | null | [
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---
# Dataset Card for "muld_AO3_Style_Change_Detection"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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shunk031/cocostuff | shunk031 | 2022-12-09T04:29:27Z | 12 | 0 | null | [
"language:en",
"license:cc-by-4.0",
"computer-vision",
"object-detection",
"ms-coco",
"arxiv:1612.03716",
"region:us"
] | 2022-12-09T04:29:27Z | 2022-11-02T17:47:27.000Z | 2022-11-02T17:47:27 | ---
language:
- en
license: cc-by-4.0
tags:
- computer-vision
- object-detection
- ms-coco
datasets:
- stuff-thing
- stuff-only
metrics:
- accuracy
- iou
---
# Dataset Card for COCO-Stuff
[](https://github.com/shunk031/huggingface-datasets_cocostuff/actions/workflows/ci.yaml)
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Dataset Preprocessing](#dataset-preprocessing)
- [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: https://github.com/nightrome/cocostuff
- Repository: https://github.com/nightrome/cocostuff
- Paper (preprint): https://arxiv.org/abs/1612.03716
- Paper (CVPR2018): https://openaccess.thecvf.com/content_cvpr_2018/html/Caesar_COCO-Stuff_Thing_and_CVPR_2018_paper.html
### Dataset Summary
COCO-Stuff is the largest existing dataset with dense stuff and thing annotations.
From the paper:
> Semantic classes can be either things (objects with a well-defined shape, e.g. car, person) or stuff (amorphous background regions, e.g. grass, sky). While lots of classification and detection works focus on thing classes, less attention has been given to stuff classes. Nonetheless, stuff classes are important as they allow to explain important aspects of an image, including (1) scene type; (2) which thing classes are likely to be present and their location (through contextual reasoning); (3) physical attributes, material types and geometric properties of the scene. To understand stuff and things in context we introduce COCO-Stuff, which augments all 164K images of the COCO 2017 dataset with pixel-wise annotations for 91 stuff classes. We introduce an efficient stuff annotation protocol based on superpixels, which leverages the original thing annotations. We quantify the speed versus quality trade-off of our protocol and explore the relation between annotation time and boundary complexity. Furthermore, we use COCO-Stuff to analyze: (a) the importance of stuff and thing classes in terms of their surface cover and how frequently they are mentioned in image captions; (b) the spatial relations between stuff and things, highlighting the rich contextual relations that make our dataset unique; (c) the performance of a modern semantic segmentation method on stuff and thing classes, and whether stuff is easier to segment than things.
### Dataset Preprocessing
### Supported Tasks and Leaderboards
### Languages
All of annotations use English as primary language.
## Dataset Structure
### Data Instances
When loading a specific configuration, users has to append a version dependent suffix:
```python
from datasets import load_dataset
load_dataset("shunk031/cocostuff", "stuff-thing")
```
#### stuff-things
An example of looks as follows.
```json
{
'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=640x480 at 0x7FCA033C9C40>,
'image_filename': '000000000009.jpg',
'image_id': '9',
'width': 640
'height': 480,
'objects': [
{
'object_id': '121',
'x': 0,
'y': 11,
'w': 640,
'h': 469,
'name': 'food-other'
},
{
'object_id': '143',
'x': 0,
'y': 0
'w': 640,
'h': 480,
'name': 'plastic'
},
{
'object_id': '165',
'x': 0,
'y': 0,
'w': 319,
'h': 118,
'name': 'table'
},
{
'object_id': '183',
'x': 0,
'y': 2,
'w': 631,
'h': 472,
'name': 'unknown-183'
}
],
'stuff_map': <PIL.PngImagePlugin.PngImageFile image mode=L size=640x480 at 0x7FCA0222D880>,
}
```
#### stuff-only
An example of looks as follows.
```json
{
'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=640x480 at 0x7FCA033C9C40>,
'image_filename': '000000000009.jpg',
'image_id': '9',
'width': 640
'height': 480,
'objects': [
{
'object_id': '121',
'x': 0,
'y': 11,
'w': 640,
'h': 469,
'name': 'food-other'
},
{
'object_id': '143',
'x': 0,
'y': 0
'w': 640,
'h': 480,
'name': 'plastic'
},
{
'object_id': '165',
'x': 0,
'y': 0,
'w': 319,
'h': 118,
'name': 'table'
},
{
'object_id': '183',
'x': 0,
'y': 2,
'w': 631,
'h': 472,
'name': 'unknown-183'
}
]
}
```
### Data Fields
#### stuff-things
- `image`: A `PIL.Image.Image` object containing the image.
- `image_id`: Unique numeric ID of the image.
- `image_filename`: File name of the image.
- `width`: Image width.
- `height`: Image height.
- `stuff_map`: A `PIL.Image.Image` object containing the Stuff + thing PNG-style annotations
- `objects`: Holds a list of `Object` data classes:
- `object_id`: Unique numeric ID of the object.
- `x`: x coordinate of bounding box's top left corner.
- `y`: y coordinate of bounding box's top left corner.
- `w`: Bounding box width.
- `h`: Bounding box height.
- `name`: object name
#### stuff-only
- `image`: A `PIL.Image.Image` object containing the image.
- `image_id`: Unique numeric ID of the image.
- `image_filename`: File name of the image.
- `width`: Image width.
- `height`: Image height.
- `objects`: Holds a list of `Object` data classes:
- `object_id`: Unique numeric ID of the object.
- `x`: x coordinate of bounding box's top left corner.
- `y`: y coordinate of bounding box's top left corner.
- `w`: Bounding box width.
- `h`: Bounding box height.
- `name`: object name
### Data Splits
| name | train | validation |
|-------------|--------:|-----------:|
| stuff-thing | 118,280 | 5,000 |
| stuff-only | 118,280 | 5,000 |
## Dataset Creation
### Curation Rationale
### Source Data
#### Initial Data Collection and Normalization
#### Who are the source language producers?
### Annotations
#### Annotation process
#### Who are the annotators?
From the paper:
> COCO-Stuff contains 172 classes: 80 thing, 91 stuff, and 1 class unlabeled. The 80 thing classes are the same as in COCO [35]. The 91 stuff classes are curated by an expert annotator. The class unlabeled is used in two situations: if a label does not belong to any of the 171 predefined classes, or if the annotator cannot infer the label of a pixel.
### Personal and Sensitive Information
## Considerations for Using the Data
### Social Impact of Dataset
### Discussion of Biases
### Other Known Limitations
## Additional Information
### Dataset Curators
### Licensing Information
COCO-Stuff is a derivative work of the COCO dataset. The authors of COCO do not in any form endorse this work. Different licenses apply:
- COCO images: [Flickr Terms of use](http://cocodataset.org/#termsofuse)
- COCO annotations: [Creative Commons Attribution 4.0 License](http://cocodataset.org/#termsofuse)
- COCO-Stuff annotations & code: [Creative Commons Attribution 4.0 License](http://cocodataset.org/#termsofuse)
### Citation Information
```bibtex
@INPROCEEDINGS{caesar2018cvpr,
title={COCO-Stuff: Thing and stuff classes in context},
author={Caesar, Holger and Uijlings, Jasper and Ferrari, Vittorio},
booktitle={Computer vision and pattern recognition (CVPR), 2018 IEEE conference on},
organization={IEEE},
year={2018}
}
```
### Contributions
Thanks to [@nightrome](https://github.com/nightrome) for publishing the COCO-Stuff dataset.
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license: artistic-2.0
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dataset_info:
features:
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splits:
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num_bytes: 6221323762.0
num_examples: 10000
download_size: 5912620994
dataset_size: 6221323762.0
---
# Dataset Card for "diffusiondb_random_10k"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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license: creativeml-openrail-m
---
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dreamproit/bill_summary_us | dreamproit | 2023-10-17T04:16:57Z | 12 | 4 | null | [
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annotations_creators:
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language:
- en
language_creators:
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multilinguality:
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pretty_name: bill_summary_us
size_categories:
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source_datasets:
- original
tags:
- bills
- legal
task_categories:
- summarization
task_ids: []
configs:
- config_name: default
---
# Dataset Card for "bill_summary_us"
## 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:** [BillML](https://github.com/dreamproit/BillML)
- **Repository:** [BillML](https://github.com/dreamproit/BillML)
- **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Leaderboard:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
### Dataset Summary
Dataset for summarization of summarization of US Congressional bills (bill_summary_us).
### Supported Tasks and Leaderboards
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
### Languages
English
## Dataset Structure
### Data Instances
#### default
### Data Fields
- id: id of the bill in format(congress number + bill type + bill number + bill version).
- congress: number of the congress.
- bill_type: type of the bill.
- bill_number: number of the bill.
- bill_version: version of the bill.
- sections: list of bill sections with section_id, text and header.
- sections_length: number with lenght of the sections list.
- text: bill text.
- text_length: number of characters in the text.
- summary: summary of the bill.
- summary_length: number of characters in the summary.
- title: official title of the bill.
### Data Splits
train
## Dataset Creation
### Curation Rationale
Bills (proposed laws) are specialized, structured documents with great public significance. Often, the language of a bill may not directly explain the potential impact of the legislation. For bills in the U.S. Congress, the Congressional Research Service of the Library of Congress provides professional, non-partisan summaries of bills. These are valuable for public understanding of the bills and are serve as an essential part of the lawmaking process to understand the meaning and potential legislative impact.
This dataset collects the text of bills, some metadata, as well as the CRS summaries. In order to build more accurate ML models for bill summarization it is important to have a clean dataset, alongside the professionally-written CRS summaries. ML summarization models built on generic data are bound to produce less accurate results (sometimes creating summaries that describe the opposite of a bill's actual effect). In addition, models that attempt to summarize all bills (some of which may reach 4000 pages long) may also be inaccurate due to the current limitations of summarization on long texts.
As a result, this dataset collects bill and summary information; it provides text as a list of sections with the text and header. This could be used to create a summary of sections and then a summary of summaries.
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
### Source Data
[govinfo.gov](https://www.govinfo.gov/)
#### Initial Data Collection and Normalization
The data consists of the US congress bills that were collected from the [govinfo.gov](https://www.govinfo.gov/) service provided by the United States Government Publishing Office (GPO) under CC0-1.0 license.
#### Who are the source language producers?
[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
### 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
[dreamproit.com](https://dreamproit.com/)
### Licensing Information
Bill and summary information are public and are unlicensed, as it is data produced by government entities. The collection and enhancement work that we provide for this dataset, to the degree it may be covered by copyright, is released under [CC0](https://creativecommons.org/share-your-work/public-domain/cc0/).
### Citation Information
[More Information Needed]
### Contributions
Thanks to [@aih](https://github.com/aih) [@BorodaUA](https://github.com/BorodaUA), [@alexbojko](https://github.com/alexbojko) for adding this dataset. | [
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license: apache-2.0
---
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---
# Dataset Card for "stereoset_zero"
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---
# Dataset Card for "gal_yair_8300_256x256"
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-0.52829909324646,
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-0.9104477167129517,
0.5715674161911011,
-... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
bigbio/ask_a_patient | bigbio | 2022-12-22T15:43:18Z | 12 | 1 | null | [
"multilinguality:monolingual",
"language:en",
"license:cc-by-4.0",
"region:us"
] | 2022-12-22T15:43:18Z | 2022-11-13T18:26:06.000Z | 2022-11-13T18:26:06 |
---
language:
- en
bigbio_language:
- English
license: cc-by-4.0
multilinguality: monolingual
bigbio_license_shortname: CC_BY_4p0
pretty_name: AskAPatient
homepage: https://zenodo.org/record/55013
bigbio_pubmed: True
bigbio_public: True
bigbio_tasks:
- NAMED_ENTITY_RECOGNITION
- NAMED_ENTITY_DISAMBIGUATION
---
# Dataset Card for AskAPatient
## Dataset Description
- **Homepage:** https://zenodo.org/record/55013
- **Pubmed:** True
- **Public:** True
- **Tasks:** NER,NED
The AskAPatient dataset contains medical concepts written on social media mapped to how they are formally written in medical ontologies (SNOMED-CT and AMT).
## Citation Information
```
@inproceedings{limsopatham-collier-2016-normalising,
title = "Normalising Medical Concepts in Social Media Texts by Learning Semantic Representation",
author = "Limsopatham, Nut and
Collier, Nigel",
booktitle = "Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
month = aug,
year = "2016",
address = "Berlin, Germany",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/P16-1096",
doi = "10.18653/v1/P16-1096",
pages = "1014--1023",
}
```
| [
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0.3580169975757599,
... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
bigbio/geokhoj_v1 | bigbio | 2022-12-22T15:44:42Z | 12 | 0 | null | [
"multilinguality:monolingual",
"language:en",
"license:cc-by-nc-4.0",
"region:us"
] | 2022-12-22T15:44:42Z | 2022-11-13T22:08:46.000Z | 2022-11-13T22:08:46 |
---
language:
- en
bigbio_language:
- English
license: cc-by-nc-4.0
multilinguality: monolingual
bigbio_license_shortname: CC_BY_NC_4p0
pretty_name: GEOKhoj v1
homepage: https://github.com/ElucidataInc/GEOKhoj-datasets/tree/main/geokhoj_v1
bigbio_pubmed: False
bigbio_public: True
bigbio_tasks:
- TEXT_CLASSIFICATION
---
# Dataset Card for GEOKhoj v1
## Dataset Description
- **Homepage:** https://github.com/ElucidataInc/GEOKhoj-datasets/tree/main/geokhoj_v1
- **Pubmed:** False
- **Public:** True
- **Tasks:** TXTCLASS
GEOKhoj v1 is a annotated corpus of control/perturbation labels for 30,000 samples
from Microarray, Transcriptomics and Single cell experiments which are available on
the GEO (Gene Expression Omnibus) database
## Citation Information
```
@misc{geokhoj_v1,
author = {Elucidata, Inc.},
title = {GEOKhoj v1},
howpublished = {\url{https://github.com/ElucidataInc/GEOKhoj-datasets/tree/main/geokhoj_v1}},
}
```
| [
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0.04497072100639343,
... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
bigbio/minimayosrs | bigbio | 2022-12-22T15:45:36Z | 12 | 1 | null | [
"multilinguality:monolingual",
"language:en",
"license:cc0-1.0",
"region:us"
] | 2022-12-22T15:45:36Z | 2022-11-13T22:09:56.000Z | 2022-11-13T22:09:56 |
---
language:
- en
bigbio_language:
- English
license: cc0-1.0
multilinguality: monolingual
bigbio_license_shortname: CC0_1p0
pretty_name: MiniMayoSRS
homepage: https://conservancy.umn.edu/handle/11299/196265
bigbio_pubmed: False
bigbio_public: True
bigbio_tasks:
- SEMANTIC_SIMILARITY
---
# Dataset Card for MiniMayoSRS
## Dataset Description
- **Homepage:** https://conservancy.umn.edu/handle/11299/196265
- **Pubmed:** False
- **Public:** True
- **Tasks:** STS
MiniMayoSRS is a subset of the MayoSRS and consists of 30 term pairs on which a higher inter-annotator agreement was
achieved. The average correlation between physicians is 0.68. The average correlation between medical coders is 0.78.
## Citation Information
```
@article{pedersen2007measures,
title={Measures of semantic similarity and relatedness in the biomedical domain},
author={Pedersen, Ted and Pakhomov, Serguei VS and Patwardhan, Siddharth and Chute, Christopher G},
journal={Journal of biomedical informatics},
volume={40},
number={3},
pages={288--299},
year={2007},
publisher={Elsevier}
}
```
| [
-0.3558613359928131,
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0.5848588943481445,
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-0.5993807315826416,
-0.8348207473754883,
0.303839802742004... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
bigbio/n2c2_2008 | bigbio | 2022-12-22T15:45:48Z | 12 | 0 | null | [
"multilinguality:monolingual",
"language:en",
"license:other",
"region:us"
] | 2022-12-22T15:45:48Z | 2022-11-13T22:10:28.000Z | 2022-11-13T22:10:28 |
---
language:
- en
bigbio_language:
- English
license: other
multilinguality: monolingual
bigbio_license_shortname: DUA
pretty_name: n2c2 2008 Obesity
homepage: https://portal.dbmi.hms.harvard.edu/projects/n2c2-nlp/
bigbio_pubmed: True
bigbio_public: False
bigbio_tasks:
- TEXT_CLASSIFICATION
---
# Dataset Card for n2c2 2008 Obesity
## Dataset Description
- **Homepage:** https://portal.dbmi.hms.harvard.edu/projects/n2c2-nlp/
- **Pubmed:** True
- **Public:** False
- **Tasks:** TXTCLASS
The data for the n2c2 2008 obesity challenge consisted of discharge summaries from
the Partners HealthCare Research Patient Data Repository. These data were chosen
from the discharge summaries of patients who were overweight or diabetic and had
been hospitalized for obesity or diabetes sometime since 12/1/04. De-identification
was performed semi-automatically. All private health information was replaced with
synthetic identifiers.
The data for the challenge were annotated by two obesity experts from the
Massachusetts General Hospital Weight Center. The experts were given a textual task,
which asked them to classify each disease (see list of diseases above) as Present,
Absent, Questionable, or Unmentioned based on explicitly documented information in
the discharge summaries, e.g., the statement “the patient is obese”. The experts were
also given an intuitive task, which asked them to classify each disease as Present,
Absent, or Questionable by applying their intuition and judgment to information in
the discharge summaries.
## Citation Information
```
@article{uzuner2009recognizing,
author = {
Uzuner, Ozlem
},
title = {Recognizing Obesity and Comorbidities in Sparse Data},
journal = {Journal of the American Medical Informatics Association},
volume = {16},
number = {4},
pages = {561-570},
year = {2009},
month = {07},
url = {https://doi.org/10.1197/jamia.M3115},
doi = {10.1197/jamia.M3115},
eprint = {https://academic.oup.com/jamia/article-pdf/16/4/561/2302602/16-4-561.pdf}
}
```
| [
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0.2701174616... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
Den4ikAI/mailruQA-big | Den4ikAI | 2022-11-18T04:08:50Z | 12 | 2 | null | [
"license:mit",
"region:us"
] | 2022-11-18T04:08:50Z | 2022-11-14T23:23:53.000Z | 2022-11-14T23:23:53 | ---
license: mit
---
Обработан из 54 гигабайт данных. Удалены имена, не используются ответы больше 100 символов. | [
-0.15338784456253052,
-0.6277005076408386,
0.31206563115119934,
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-0.6185635328292847,
-0.13692246377468... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
dlwh/eu_wikipedias | dlwh | 2022-11-17T08:13:51Z | 12 | 0 | null | [
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:language-modeling",
"task_ids:masked-language-modeling",
"annotations_creators:no-annotation",
"language_creators:crowdsourced",
"multilinguality:multilingual",
"size_categories:n<1K",
"size_categories:1K<n<10K",
"size_categ... | 2022-11-17T08:13:51Z | 2022-11-16T18:03:07.000Z | 2022-11-16T18:03:07 | ---
annotations_creators:
- no-annotation
language_creators:
- crowdsourced
pretty_name: Wikipedia
paperswithcode_id: null
license:
- cc-by-sa-3.0
- gfdl
task_categories:
- text-generation
- fill-mask
task_ids:
- language-modeling
- masked-language-modeling
source_datasets:
- original
multilinguality:
- multilingual
size_categories:
- n<1K
- 1K<n<10K
- 10K<n<100K
- 100K<n<1M
- 1M<n<10M
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
---
# Dataset Card for Wikipedia
This repo is a wrapper around [olm/wikipedia](https://huggingface.co/datasets/olm/wikipedia) that just concatenates data from the EU languages.
Please refer to it for a complete data card.
The EU languages we include are:
- bg
- cs
- da
- de
- el
- en
- es
- et
- fi
- fr
- ga
- hr
- hu
- it
- lt
- lv
- mt
- nl
- pl
- pt
- ro
- sk
- sl
- sv
As with `olm/wikipedia` you will need to install a few dependencies:
```
pip install mwparserfromhell==0.6.4 multiprocess==0.70.13
```
```python
from datasets import load_dataset
load_dataset("dlwh/eu_wikipedias", date="20221101")
```
Please refer to the original olm/wikipedia for a complete data card.
| [
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-0.3135104179382324,
0.39568147063... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
gluten/gpk-captions | gluten | 2022-11-20T04:03:10Z | 12 | 0 | null | [
"doi:10.57967/hf/0123",
"region:us"
] | 2022-11-20T04:03:10Z | 2022-11-20T03:42:14.000Z | 2022-11-20T03:42:14 | ---
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
splits:
- name: train
num_bytes: 45126936.0
num_examples: 83
download_size: 45128569
dataset_size: 45126936.0
---
# Dataset Card for "gpk-captions"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
-0.5578928589820862,
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-0.043190695345401... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
DTU54DL/common-voice-test16k | DTU54DL | 2022-11-21T13:49:22Z | 12 | 0 | acronym-identification | [
"task_categories:token-classification",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:mit",
"region:us"
] | 2022-11-21T13:49:22Z | 2022-11-20T15:31:49.000Z | 2022-11-20T15:31:49 | ---
annotations_creators:
- expert-generated
language:
- en
language_creators:
- found
license:
- mit
multilinguality:
- monolingual
paperswithcode_id: acronym-identification
pretty_name: Acronym Identification Dataset
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- token-classification-other-acronym-identification
train-eval-index:
- col_mapping:
labels: tags
tokens: tokens
config: default
splits:
eval_split: test
task: token-classification
task_id: entity_extraction
dataset_info:
features:
- name: audio
dtype:
audio:
sampling_rate: 16000
- name: sentence
dtype: string
- name: accent
dtype: string
splits:
- name: test
num_bytes: 710805761.334
num_examples: 16354
download_size: 701898414
dataset_size: 710805761.334
---
# 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
[More Information Needed]
### Supported Tasks and Leaderboards
[More Information Needed]
### Languages
[More Information Needed]
## Dataset Structure
### Data Instances
[More Information Needed]
### Data Fields
[More Information Needed]
### Data Splits
[More Information Needed]
## 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. | [
-0.47841677069664,
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-0.7551794052124023,
0.07273735105991364,
... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
yuvalkirstain/pokemon-split | yuvalkirstain | 2022-11-20T16:32:00Z | 12 | 1 | null | [
"region:us"
] | 2022-11-20T16:32:00Z | 2022-11-20T16:29:18.000Z | 2022-11-20T16:29:18 | ---
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
splits:
- name: train
num_bytes: 107374569.23529412
num_examples: 749
- name: test
num_bytes: 12042007.764705881
num_examples: 84
download_size: 99425904
dataset_size: 119416577.0
---
# Dataset Card for "pokemon-split"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
-0.714238166809082,
-0.2728690505027771,
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-0.567755401134491,
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... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
autoevaluate/autoeval-staging-eval-project-977d15c2-b4b7-4875-aee0-490ae596d0f4-3432 | autoevaluate | 2022-11-21T10:16:21Z | 12 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T10:16:21Z | 2022-11-21T10:15:43.000Z | 2022-11-21T10:15:43 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- glue
eval_info:
task: binary_classification
model: autoevaluate/binary-classification
metrics: ['matthews_correlation']
dataset_name: glue
dataset_config: sst2
dataset_split: validation
col_mapping:
text: sentence
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: Binary Text Classification
* Model: autoevaluate/binary-classification
* Dataset: glue
* Config: sst2
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | [
-0.20361600816249847,
-0.33383119106292725,
0.2989136576652527,
0.17618101835250854,
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-0.770520806312561,
-0.01348811481... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
autoevaluate/autoeval-staging-eval-project-6a3804e2-ad4c-48af-8aa6-4620beed26ac-3533 | autoevaluate | 2022-11-21T10:19:04Z | 12 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T10:19:04Z | 2022-11-21T10:18:27.000Z | 2022-11-21T10:18:27 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- glue
eval_info:
task: binary_classification
model: autoevaluate/binary-classification
metrics: ['matthews_correlation']
dataset_name: glue
dataset_config: sst2
dataset_split: validation
col_mapping:
text: sentence
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: Binary Text Classification
* Model: autoevaluate/binary-classification
* Dataset: glue
* Config: sst2
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | [
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-0.01348786149... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
autoevaluate/autoeval-staging-eval-project-d545d554-fb32-43d5-a9dd-4a47f0efba15-3836 | autoevaluate | 2022-11-21T10:52:16Z | 12 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T10:52:16Z | 2022-11-21T10:51:40.000Z | 2022-11-21T10:51:40 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- glue
eval_info:
task: binary_classification
model: autoevaluate/binary-classification
metrics: ['matthews_correlation']
dataset_name: glue
dataset_config: sst2
dataset_split: validation
col_mapping:
text: sentence
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: Binary Text Classification
* Model: autoevaluate/binary-classification
* Dataset: glue
* Config: sst2
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | [
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nlhappy/CHIP-TC | nlhappy | 2022-11-21T11:00:42Z | 12 | 0 | null | [
"license:mit",
"region:us"
] | 2022-11-21T11:00:42Z | 2022-11-21T10:59:59.000Z | 2022-11-21T10:59:59 | ---
license: mit
---
| [
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autoevaluate/autoeval-staging-eval-project-408e9b4e-b238-40e9-a460-4dacc071ae0d-3937 | autoevaluate | 2022-11-21T11:08:40Z | 12 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T11:08:40Z | 2022-11-21T11:08:03.000Z | 2022-11-21T11:08:03 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- glue
eval_info:
task: binary_classification
model: autoevaluate/binary-classification
metrics: ['matthews_correlation']
dataset_name: glue
dataset_config: sst2
dataset_split: validation
col_mapping:
text: sentence
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: Binary Text Classification
* Model: autoevaluate/binary-classification
* Dataset: glue
* Config: sst2
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | [
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polinaeterna/test_push_new | polinaeterna | 2022-11-21T11:16:30Z | 12 | 0 | null | [
"region:us"
] | 2022-11-21T11:16:30Z | 2022-11-21T11:15:45.000Z | 2022-11-21T11:15:45 | ---
dataset_info:
- config_name: v3
features:
- name: x
dtype: int64
- name: y
dtype: string
splits:
- name: train
num_bytes: 74
num_examples: 5
- name: test
num_bytes: 88
num_examples: 6
download_size: 1704
dataset_size: 162
---
# Dataset Card for "test_push_new"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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autoevaluate/autoeval-staging-eval-project-a3656eb0-b7ed-410f-ab65-0222b8e06770-4139 | autoevaluate | 2022-11-21T11:21:43Z | 12 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T11:21:43Z | 2022-11-21T11:21:05.000Z | 2022-11-21T11:21:05 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- glue
eval_info:
task: binary_classification
model: autoevaluate/binary-classification
metrics: ['matthews_correlation']
dataset_name: glue
dataset_config: sst2
dataset_split: validation
col_mapping:
text: sentence
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: Binary Text Classification
* Model: autoevaluate/binary-classification
* Dataset: glue
* Config: sst2
* Split: validation
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | [
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autoevaluate/autoeval-staging-eval-project-e8ce9c11-cb63-47ba-8b24-d3a9a8e15a88-4240 | autoevaluate | 2022-11-21T11:26:20Z | 12 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T11:26:20Z | 2022-11-21T11:25:31.000Z | 2022-11-21T11:25:31 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- emotion
eval_info:
task: multi_class_classification
model: autoevaluate/multi-class-classification
metrics: ['matthews_correlation']
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: autoevaluate/multi-class-classification
* 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 [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | [
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0.04980408027768... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
autoevaluate/autoeval-staging-eval-project-b2b60f7a-3ccf-4daf-af67-2833dd712c28-5048 | autoevaluate | 2022-11-21T13:09:34Z | 12 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T13:09:34Z | 2022-11-21T13:08:52.000Z | 2022-11-21T13:08:52 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- emotion
eval_info:
task: multi_class_classification
model: autoevaluate/multi-class-classification
metrics: ['matthews_correlation']
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: autoevaluate/multi-class-classification
* 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 [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | [
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0.04980408027768... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
autoevaluate/autoeval-staging-eval-project-e438add5-1e56-41ec-9c26-2ad4182383b0-6260 | autoevaluate | 2022-11-21T14:28:17Z | 12 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T14:28:17Z | 2022-11-21T14:27:41.000Z | 2022-11-21T14:27:41 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- autoevaluate/squad-sample
eval_info:
task: extractive_question_answering
model: autoevaluate/extractive-question-answering
metrics: []
dataset_name: autoevaluate/squad-sample
dataset_config: autoevaluate--squad-sample
dataset_split: test
col_mapping:
context: context
question: question
answers-text: answers.text
answers-answer_start: answers.answer_start
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Question Answering
* Model: autoevaluate/extractive-question-answering
* Dataset: autoevaluate/squad-sample
* Config: autoevaluate--squad-sample
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | [
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0.08177109807729... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
autoevaluate/autoeval-staging-eval-project-b40c7dea-3c58-4f26-a941-b0221649edda-6362 | autoevaluate | 2022-11-21T14:35:26Z | 12 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T14:35:26Z | 2022-11-21T14:34:51.000Z | 2022-11-21T14:34:51 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- autoevaluate/xsum-sample
eval_info:
task: summarization
model: autoevaluate/summarization
metrics: []
dataset_name: autoevaluate/xsum-sample
dataset_config: autoevaluate--xsum-sample
dataset_split: test
col_mapping:
text: document
target: summary
---
# 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: autoevaluate/summarization
* Dataset: autoevaluate/xsum-sample
* Config: autoevaluate--xsum-sample
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | [
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autoevaluate/autoeval-staging-eval-project-b07c55ed-3514-4853-9004-f2d3a7737d92-6564 | autoevaluate | 2022-11-21T14:49:16Z | 12 | 0 | null | [
"autotrain",
"evaluation",
"region:us"
] | 2022-11-21T14:49:16Z | 2022-11-21T14:48:30.000Z | 2022-11-21T14:48:30 | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- autoevaluate/wmt16-ro-en-sample
eval_info:
task: translation
model: autoevaluate/translation
metrics: []
dataset_name: autoevaluate/wmt16-ro-en-sample
dataset_config: autoevaluate--wmt16-ro-en-sample
dataset_split: test
col_mapping:
source: translation.ro
target: translation.en
---
# Dataset Card for AutoTrain Evaluator
This repository contains model predictions generated by [AutoTrain](https://huggingface.co/autotrain) for the following task and dataset:
* Task: Translation
* Model: autoevaluate/translation
* Dataset: autoevaluate/wmt16-ro-en-sample
* Config: autoevaluate--wmt16-ro-en-sample
* Split: test
To run new evaluation jobs, visit Hugging Face's [automatic model evaluator](https://huggingface.co/spaces/autoevaluate/model-evaluator).
## Contributions
Thanks to [@lewtun](https://huggingface.co/lewtun) for evaluating this model. | [
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0.077527813613... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
2dchaos/test | 2dchaos | 2022-11-21T17:45:39Z | 12 | 0 | null | [
"license:unknown",
"region:us"
] | 2022-11-21T17:45:39Z | 2022-11-21T17:45:02.000Z | 2022-11-21T17:45:02 | ---
license: unknown
---
| [
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AJRFan/Incredibox_Characters | AJRFan | 2022-12-26T20:47:10Z | 12 | 0 | null | [
"license:artistic-2.0",
"region:us"
] | 2022-12-26T20:47:10Z | 2022-11-21T20:23:16.000Z | 2022-11-21T20:23:16 | ---
license: artistic-2.0
---
| [
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DTU54DL/libri_augmented_train_set | DTU54DL | 2022-11-22T18:34:11Z | 12 | 0 | null | [
"region:us"
] | 2022-11-22T18:34:11Z | 2022-11-22T05:49:10.000Z | 2022-11-22T05:49:10 | ---
dataset_info:
features:
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dtype: string
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dtype:
audio:
sampling_rate: 16000
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dtype: string
splits:
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num_bytes: 41931835349.25
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download_size: 0
dataset_size: 41931835349.25
---
# Dataset Card for "libri_augmented_train_set"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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davanstrien/scottishdirectories | davanstrien | 2022-11-22T10:30:56Z | 12 | 0 | null | [
"region:us"
] | 2022-11-22T10:30:56Z | 2022-11-22T10:30:50.000Z | 2022-11-22T10:30:50 | ---
dataset_info:
features:
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splits:
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num_bytes: 166317574
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download_size: 13810640
dataset_size: 166317574
---
# Dataset Card for "scottishdirectories"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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Matthewww/nyt_news | Matthewww | 2022-11-23T01:52:10Z | 12 | 0 | null | [
"region:us"
] | 2022-11-23T01:52:10Z | 2022-11-23T00:23:28.000Z | 2022-11-23T00:23:28 | Entry not found | [
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Una713/description2Image | Una713 | 2022-11-23T23:52:33Z | 12 | 0 | null | [
"region:us"
] | 2022-11-23T23:52:33Z | 2022-11-23T00:54:30.000Z | 2022-11-23T00:54:30 | ---
dataset_info:
features:
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dtype: image
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splits:
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num_bytes: 9546659.0
num_examples: 335
download_size: 5446356
dataset_size: 9546659.0
---
# Dataset Card for "description2Image"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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arbml/ARGEN_title_generation | arbml | 2022-11-23T02:31:30Z | 12 | 0 | null | [
"region:us"
] | 2022-11-23T02:31:30Z | 2022-11-23T02:31:19.000Z | 2022-11-23T02:31:19 | ---
dataset_info:
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---
# Dataset Card for "ARGEN_title_generation"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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carlosejimenez/mnli_corpus_trainval | carlosejimenez | 2022-11-23T02:37:49Z | 12 | 0 | null | [
"region:us"
] | 2022-11-23T02:37:49Z | 2022-11-23T02:37:09.000Z | 2022-11-23T02:37:09 | ---
dataset_info:
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---
# Dataset Card for "mnli_corpus_trainval"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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carlosejimenez/qqp_corpus_trainval | carlosejimenez | 2022-11-23T06:00:08Z | 12 | 0 | null | [
"region:us"
] | 2022-11-23T06:00:08Z | 2022-11-23T05:59:55.000Z | 2022-11-23T05:59:55 | ---
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---
# Dataset Card for "qqp_corpus_trainval"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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LIXXX/ibm_debate | LIXXX | 2022-11-23T09:02:34Z | 12 | 0 | null | [
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Deepak2846/Name_mini | Deepak2846 | 2022-11-23T10:51:02Z | 12 | 0 | null | [
"region:us"
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VishwanathanR/flowers-dataset | VishwanathanR | 2022-11-23T14:08:09Z | 12 | 0 | null | [
"region:us"
] | 2022-11-23T14:08:09Z | 2022-11-23T14:05:29.000Z | 2022-11-23T14:05:29 | ---
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---
# Dataset Card for "flowers-dataset"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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loubnabnl/python_comment_code_ratio_08 | loubnabnl | 2022-11-23T16:02:40Z | 12 | 1 | null | [
"region:us"
] | 2022-11-23T16:02:40Z | 2022-11-23T16:02:32.000Z | 2022-11-23T16:02:32 | ---
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---
# Dataset Card for "python_comment_code_ratio_08"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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channotte/Georges_Sand | channotte | 2022-11-25T13:21:17Z | 12 | 0 | null | [
"region:us"
] | 2022-11-25T13:21:17Z | 2022-11-23T16:35:52.000Z | 2022-11-23T16:35:52 | ---
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---
# Dataset Card for "Georges_Sand"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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priyank-m/word_based_IAM_SROIE_text_recognition | priyank-m | 2022-11-23T17:29:21Z | 12 | 0 | null | [
"region:us"
] | 2022-11-23T17:29:21Z | 2022-11-23T17:28:23.000Z | 2022-11-23T17:28:23 | ---
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---
# Dataset Card for "word_based_IAM_SROIE_text_recognition"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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Joehighlord/Amity-Blight | Joehighlord | 2022-11-23T17:42:50Z | 12 | 0 | null | [
"license:cc",
"region:us"
] | 2022-11-23T17:42:50Z | 2022-11-23T17:41:31.000Z | 2022-11-23T17:41:31 | ---
license: cc
---
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gldalessandro/FiguresSD | gldalessandro | 2022-11-23T19:02:48Z | 12 | 0 | null | [
"license:unknown",
"region:us"
] | 2022-11-23T19:02:48Z | 2022-11-23T18:56:55.000Z | 2022-11-23T18:56:55 | ---
license: unknown
---
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pszemraj/booksum-1024-output | pszemraj | 2023-11-21T13:15:10Z | 12 | 0 | null | [
"task_categories:summarization",
"task_categories:text2text-generation",
"size_categories:1K<n<10K",
"source_datasets:kmfoda/booksum",
"license:bsd-3-clause",
"region:us"
] | 2023-11-21T13:15:10Z | 2022-11-23T20:02:05.000Z | 2022-11-23T20:02:05 | ---
source_datasets: kmfoda/booksum
license:
- bsd-3-clause
train-eval-index:
- config: pszemraj--booksum_1024
task: summarization
task_id: summarization
splits:
eval_split: test
col_mapping:
chapter: text
summary_text: target
task_categories:
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- text2text-generation
size_categories:
- 1K<n<10K
---
# booksum - 1024 tokens max output
**goal:** limit max output length explicitly to prevent partial summaries being generated.
- [notebook](https://colab.research.google.com/gist/pszemraj/7f7b66d535441a9d0e8419fde1e1c98a/booksum-1024.ipynb) to create
## info
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amirfafa/1 | amirfafa | 2022-11-23T23:05:10Z | 12 | 0 | null | [
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] | 2022-11-23T23:05:10Z | 2022-11-23T23:04:35.000Z | 2022-11-23T23:04:35 | Entry not found | [
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NimaBoscarino/test-glue | NimaBoscarino | 2022-11-23T23:14:47Z | 12 | 0 | null | [
"region:us"
] | 2022-11-23T23:14:47Z | 2022-11-23T23:14:41.000Z | 2022-11-23T23:14:41 | ---
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---
# Dataset Card for "test-glue"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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VSPuzzler/SemevalTestingData | VSPuzzler | 2022-11-24T02:17:02Z | 12 | 0 | null | [
"region:us"
] | 2022-11-24T02:17:02Z | 2022-11-24T02:16:24.000Z | 2022-11-24T02:16:24 | Entry not found | [
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kpriyanshu256/yannic-aleksa-2min | kpriyanshu256 | 2022-11-24T03:38:35Z | 12 | 0 | null | [
"region:us"
] | 2022-11-24T03:38:35Z | 2022-11-24T03:38:29.000Z | 2022-11-24T03:38:29 | ---
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---
# Dataset Card for "yannic-aleksa-2min"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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pattern90/test4 | pattern90 | 2022-11-24T05:21:15Z | 12 | 0 | null | [
"region:us"
] | 2022-11-24T05:21:15Z | 2022-11-24T04:49:24.000Z | 2022-11-24T04:49:24 | ---
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---
# Dataset Card for "oct"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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pattern90/sidewalk-imagery | pattern90 | 2022-11-24T05:02:00Z | 12 | 0 | null | [
"region:us"
] | 2022-11-24T05:02:00Z | 2022-11-24T05:01:47.000Z | 2022-11-24T05:01:47 | ---
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---
# Dataset Card for "sidewalk-imagery"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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watermelonhydro/es_en_2999 | watermelonhydro | 2022-11-24T05:40:39Z | 12 | 1 | null | [
"region:us"
] | 2022-11-24T05:40:39Z | 2022-11-24T05:24:33.000Z | 2022-11-24T05:24:33 | ---
dataset_info:
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---
# Dataset Card for "es_en_2999"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
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0.0665880665183067... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
jojofan/minguo-style | jojofan | 2022-11-24T07:37:10Z | 12 | 0 | null | [
"region:us"
] | 2022-11-24T07:37:10Z | 2022-11-24T06:56:39.000Z | 2022-11-24T06:56:39 | Entry not found | [
-0.32276472449302673,
-0.22568407654762268,
0.8622258901596069,
0.4346148371696472,
-0.5282984972000122,
0.7012965679168701,
0.7915717363357544,
0.07618629932403564,
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-0.785281777381897,
-0.22573848068714142,
-0.9104482531547546,
0.5715669393539429,
... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
shayand/coqa_squad | shayand | 2022-11-24T07:41:30Z | 12 | 0 | null | [
"license:other",
"region:us"
] | 2022-11-24T07:41:30Z | 2022-11-24T07:20:53.000Z | 2022-11-24T07:20:53 | ---
license: other
---
| [
-0.12853392958641052,
-0.18616779148578644,
0.6529127955436707,
0.49436280131340027,
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0.050563063472509384,
0.579365611076355,
0.7400140762329102,
-0.6508104205131531,
-0.23783954977989197,
-0.7102249264717102,
-0.0478260256350... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
AlekseyKorshuk/dalio-book-handwritten-io-sorted-v2 | AlekseyKorshuk | 2022-11-24T09:16:29Z | 12 | 0 | null | [
"region:us"
] | 2022-11-24T09:16:29Z | 2022-11-24T09:10:55.000Z | 2022-11-24T09:10:55 | ---
dataset_info:
features:
- name: input_text
dtype: string
- name: output_text
dtype: string
splits:
- name: train
num_bytes: 804881.0
num_examples: 599
- name: validation
num_bytes: 540344
num_examples: 364
- name: test
num_bytes: 14786
num_examples: 10
download_size: 721129
dataset_size: 1360011.0
---
# Dataset Card for "dalio-book-handwritten-io-sorted-v2"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
-0.1617278754711151,
-0.05929051712155342,
0.1357070505619049,
0.18741722404956818,
-0.4751572906970978,
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0.39906296133995056,
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0.6151846051216125,
0.7825651168823242,
-0.8587465882301331,
-0.8246481418609619,
-0.813978910446167,
-0.3446398377418518... | null | null | null | null | null | null | null | null | null | null | null | null | null | |
shreyasharma/sentences_truth | shreyasharma | 2022-11-24T11:15:28Z | 12 | 0 | null | [
"region:us"
] | 2022-11-24T11:15:28Z | 2022-11-24T11:10:53.000Z | 2022-11-24T11:10:53 | ---
dataset_info:
features:
- name: sentences
dtype: string
- name: labels
dtype: int64
splits:
- name: train
num_bytes: 445901
num_examples: 7000
- name: test
num_bytes: 134824
num_examples: 2000
- name: val
num_bytes: 151364
num_examples: 2528
download_size: 0
dataset_size: 732089
---
# Dataset Card for "sentences_truth"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) | [
-0.19767676293849945,
-0.5584410429000854,
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0.6591293811798096,
-0.8391796350479126,
-0.8832685947418213,
-0.6456762552261353,
-0.174536198377... | null | null | null | null | null | null | null | null | null | null | null | null | null |
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