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README.md

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----
-license: mit
-language:
-- en
-paperswithcode_id: embedding-data/coco_captions
-pretty_name: coco_captions
-task_categories:
-- sentence-similarity
-- paraphrase-mining
-task_ids:
-- semantic-similarity-classification
-
----
-
-# Dataset Card for "coco_captions"
-
-## 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:** [https://cocodataset.org/#home](https://cocodataset.org/#home)
-- **Repository:** [https://github.com/cocodataset/cocodataset.github.io](https://github.com/cocodataset/cocodataset.github.io)
-- **Paper:** [More Information Needed](https://arxiv.org/abs/1405.0312)
-- **Point of Contact:** [[email protected]]([email protected])
-- **Size of downloaded dataset files:** 
-- **Size of the generated dataset:** 
-- **Total amount of disk used:** 6.32 MB
-
-### Dataset Summary
-
-COCO is a large-scale object detection, segmentation, and captioning dataset. This repo contains five captions per image; useful for sentence similarity tasks.
-
-Disclaimer: The team releasing COCO did not upload the dataset to the Hub and did not write a dataset card. 
-These steps were done by the Hugging Face team.
-
-### Supported Tasks
-
-- [Sentence Transformers](https://huggingface.co/sentence-transformers) training; useful for semantic search and sentence similarity. 
-
-### Languages
-
-- English.
-
-## Dataset Structure
-
-Each example in the dataset contains quintets of similar sentences and is formatted as a dictionary with the key "set" and a list with the sentences as "value":
-
-```
-{"set": [sentence_1, sentence_2, sentence3, sentence4, sentence5]}
-{"set": [sentence_1, sentence_2, sentence3, sentence4, sentence5]}
-...
-{"set": [sentence_1, sentence_2, sentence3, sentence4, sentence5]}
-```
-
-This dataset is useful for training Sentence Transformers models. Refer to the following post on how to train models using similar pairs of sentences.
-
-### Usage Example
-
-Install the 🤗 Datasets library with `pip install datasets` and load the dataset from the Hub with:
-
-```python
-from datasets import load_dataset
-dataset = load_dataset("embedding-data/coco_captions")
-```
-The dataset is loaded as a `DatasetDict` and has the format:
-
-```python
-DatasetDict({
-    train: Dataset({
-        features: ['set'],
-        num_rows: 82783
-    })
-})
-```
-
-Review an example `i` with:
-
-```python
-dataset["train"][i]["set"]
-```
-
-
-### Data Instances
-
-[More Information Needed](https://cocodataset.org/#format-data)
-
-### Data Splits
-
-[More Information Needed](https://cocodataset.org/#format-data)
-
-## Dataset Creation
-
-### Curation Rationale
-
-[More Information Needed](https://cocodataset.org/#home)
-
-### Source Data
-
-#### Initial Data Collection and Normalization
-
-[More Information Needed](https://cocodataset.org/#home)
-
-#### Who are the source language producers?
-
-[More Information Needed](https://cocodataset.org/#home)
-
-### Annotations
-
-#### Annotation process
-
-[More Information Needed](https://cocodataset.org/#home)
-
-#### Who are the annotators?
-
-[More Information Needed](https://cocodataset.org/#home)
-
-### Personal and Sensitive Information
-
-[More Information Needed](https://cocodataset.org/#home)
-
-## Considerations for Using the Data
-
-### Social Impact of Dataset
-
-[More Information Needed](https://cocodataset.org/#home)
-
-### Discussion of Biases
-
-[More Information Needed](https://cocodataset.org/#home)
-
-### Other Known Limitations
-
-[More Information Needed](https://cocodataset.org/#home)
-
-## Additional Information
-
-### Dataset Curators
-
-[More Information Needed](https://cocodataset.org/#home)
-
-### Licensing Information
-
-The annotations in this dataset along with this website belong to the COCO Consortium 
-and are licensed under a [Creative Commons Attribution 4.0 License](https://creativecommons.org/licenses/by/4.0/legalcode)
-
-### Citation Information
-
-[More Information Needed](https://cocodataset.org/#home)
-
-### Contributions
-
-Thanks to:
-
-- Tsung-Yi Lin - Google Brain
-- Genevieve Patterson - MSR, Trash TV
-- Matteo R. - Ronchi Caltech
-- Yin Cui - Google
-- Michael Maire - TTI-Chicago
-- Serge Belongie - Cornell Tech
-- Lubomir Bourdev - WaveOne, Inc.
-- Ross Girshick - FAIR
-- James Hays - Georgia Tech
-- Pietro Perona - Caltech
-- Deva Ramanan - CMU
-- Larry Zitnick - FAIR
-- Piotr Dollár - FAIR
-
-for adding this dataset.

coco_captions.jsonl.gz → embedding-data--coco_captions_quintets/json-train.parquet

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