huggingnft/etherbears
Unconditional Image Generation
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imagewidth (px) 384
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int64 20M
42.9M
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Dataset Card
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Dataset Summary
NFT images dataset for unconditional generation.
NFT collection available here.
Model is available here.
Check Space: link.
Supported Tasks and Leaderboards
How to use
How to load this dataset directly with the datasets library:
from datasets import load_dataset
dataset = load_dataset("huggingnft/etherbears")
Dataset Structure
Data Fields
The data fields are the same among all splits.
image: animagefeature.id: anintfeature.token_metadata: astrfeature.image_original_url: astrfeature.
Data Splits
Dataset Creation
Curation Rationale
Source Data
Initial Data Collection and Normalization
Who are the source language producers?
Annotations
Annotation process
Who are the annotators?
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
Citation Information
@InProceedings{huggingnft,
author={Aleksey Korshuk}
year=2022
}
About
Built by Aleksey Korshuk
For more details, visit the project repository.
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Homepage:
github.com
Repository:
github.com
Size of downloaded dataset files:
6.13 MB
Size of the auto-converted Parquet files:
6.13 MB
Number of rows:
4,950
Models trained or fine-tuned on huggingnft/etherbears