Datasets:

andandandand
/

bo_or_not

cls string	custom_metrics null	ytrue list	ypred list	confs list	weights null	ytrue_ids list	ypred_ids list	classes list	missing string
fiftyone.utils.eval.classification.ClassificationResults	null	[ "bo", "bo", "bo", "bo", "bo", "bo", "bo", "bo", "bo", "bo", "not_bo", "not_bo", "not_bo", "not_bo", "not_bo", "not_bo", "not_bo", "not_bo", "not_bo", "not_bo", "not_bo", "not_bo", "not_bo", "not_bo", "not_bo", "not_bo", "not_bo", "not_bo", "not_bo", "not_bo" ]	[ "bo", "not_bo", "not_bo", "bo", "bo", "bo", "not_bo", "bo", "bo", "bo", "not_bo", "not_bo", "not_bo", "not_bo", "not_bo", "not_bo", "not_bo", "not_bo", "not_bo", "not_bo", "not_bo", "not_bo", "not_bo", "not_bo", "not_bo", "not_bo", "not_bo", "not_bo", "not_bo", "not_bo" ]	[ 1, 1, 0.9999999997057638, 1, 0.9999998807907104, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 ]	null	[ "68fcefa81869571f6aa42b13", "68fcefa81869571f6aa42b15", "68fcefa81869571f6aa42b16", "68fcefa81869571f6aa42b17", "68fcefa81869571f6aa42b18", "68fcefa81869571f6aa42b19", "68fcefa81869571f6aa42b1a", "68fcefa81869571f6aa42b1b", "68fcefa81869571f6aa42b1c", "68fcefa81869571f6aa42b25", "68fcefa81869571f6aa42b26", "68fcefa81869571f6aa42b27", "68fcefa81869571f6aa42b28", "68fcefa81869571f6aa42b29", "68fcefa81869571f6aa42b2a", "68fcefa81869571f6aa42b2b", "68fcefa81869571f6aa42b2c", "68fcefa81869571f6aa42b2d", "68fcefa81869571f6aa42b2e", "68fcefa81869571f6aa42b2f", "68fcefa81869571f6aa42b30", "68fcefa81869571f6aa42b31", "68fcefa81869571f6aa42b32", "68fcefa81869571f6aa42b33", "68fcefa81869571f6aa42b34", "68fcefa81869571f6aa42b35", "68fcefa81869571f6aa42b36", "68fcefa81869571f6aa42b37", "68fcefa81869571f6aa42b38", "68fcefa81869571f6aa42b39" ]	[ "68fcefe91869571f6aa42efa", "68fcefe91869571f6aa42efb", "68fcefe91869571f6aa42efc", "68fcefe91869571f6aa42efd", "68fcefe91869571f6aa42efe", "68fcefe91869571f6aa42eff", "68fcefe91869571f6aa42f00", "68fcefe91869571f6aa42f01", "68fcefe91869571f6aa42f02", "68fcefe91869571f6aa42f03", "68fcefe91869571f6aa42f04", "68fcefe91869571f6aa42f05", "68fcefe91869571f6aa42f06", "68fcefe91869571f6aa42f07", "68fcefe91869571f6aa42f08", "68fcefe91869571f6aa42f09", "68fcefe91869571f6aa42f0a", "68fcefea1869571f6aa42f0b", "68fcefea1869571f6aa42f0c", "68fcefea1869571f6aa42f0d", "68fcefea1869571f6aa42f0e", "68fcefea1869571f6aa42f0f", "68fcefea1869571f6aa42f10", "68fcefea1869571f6aa42f11", "68fcefea1869571f6aa42f12", "68fcefea1869571f6aa42f13", "68fcefea1869571f6aa42f14", "68fcefea1869571f6aa42f15", "68fcefea1869571f6aa42f16", "68fcefea1869571f6aa42f17" ]	[ "bo", "not_bo" ]	(none)

Dataset Card for bo-dataset

This is a FiftyOne dataset with 169 samples.

Installation

If you haven't already, install FiftyOne:

pip install -U fiftyone

Usage

import fiftyone as fo
from fiftyone.utils.huggingface import load_from_hub

# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = load_from_hub("andandandand/bo_or_not")

# Launch the App
session = fo.launch_app(dataset)

Dataset Details

Dataset Description

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Language(s) (NLP): en
License: mit

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