Datasheet for the Pile
Paper • 2201.07311 • Published
text stringlengths 5 1.89M | meta dict | domain stringclasses 1
value |
|---|---|---|
---
abstract: 'In frequency-selective channels linear receivers enjoy significantly-reduced complexity compared with maximum likelihood receivers at the cost of performance degradation which can be in the form of a loss of the inherent frequency diversity order or reduced coding gain. This paper demonstrates that the m... | {
"pile_set_name": "ArXiv"
} | ArXiv |
---
author:
- |
The IceCube Collaboration[^1]\
[*<http://icecube.wisc.edu/collaboration/authors/icrc19_icecube>*]{}\
E-mail:
bibliography:
- 'references.bib'
title: 'Measurement of the high-energy all-flavor neutrino-nucleon cross section with IceCube'
---
Introduction {#sec:intro}
============
Neutrinos ... | {
"pile_set_name": "ArXiv"
} | ArXiv |
---
abstract: 'Let $X = \mathbb{P}(E_1) \times_C \mathbb{P}(E_2)$ where $C$ is a smooth curve and $E_1$, $E_2$ are vector bundles over $C$.In this paper we compute the pseudo effective cones of higher codimension cycles on $X$.'
address: |
Institute of Mathematical Sciences\
CIT Campus, Taramani, Chennai 600113... | {
"pile_set_name": "ArXiv"
} | ArXiv |
---
abstract: 'We classify periodically driven quantum systems on a one-dimensional lattice, where the driving process is local and subject to a chiral symmetry condition. The analysis is in terms of the unitary operator at a half-period and also covers systems in which this operator is implemented directly, and does n... | {
"pile_set_name": "ArXiv"
} | ArXiv |
---
abstract: 'Quantum backflow is a classically forbidden effect consisting in a negative flux for states with negligible negative momentum components. It has never been observed experimentally so far. We derive a general relation that connects backflow with a critical value of the particle density, paving the way for... | {
"pile_set_name": "ArXiv"
} | ArXiv |
---
abstract: 'In this paper we address the problem of efficient estimation of Sobol sensitivy indices. First, we focus on general functional integrals of conditional moments of the form ${\mathbb{E}}(\psi({\mathbb{E}}(\varphi(Y)|X)))$ where $(X,Y)$ is a random vector with joint density $f$ and $\psi$ and $\varphi$ are... | {
"pile_set_name": "ArXiv"
} | ArXiv |
"---\nabstract: |\n When independent Bose-Einstein condensates (BEC), described quantum mechanica(...TRUNCATED) | {
"pile_set_name": "ArXiv"
} | ArXiv |
"---\nabstract: 'We examine Dirac’s early algebraic approach which introduces the [*standard*]{} k(...TRUNCATED) | {
"pile_set_name": "ArXiv"
} | ArXiv |
"---\nabstract: 'In various interaction tasks using Underwater Vehicle Manipulator Systems (UVMSs) ((...TRUNCATED) | {
"pile_set_name": "ArXiv"
} | ArXiv |
"---\nabstract: |\n The portfolio are a critical factor not only in risk analysis, but also in in(...TRUNCATED) | {
"pile_set_name": "ArXiv"
} | ArXiv |
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Dataset description
The pile is an 800GB dataset of english text designed by EleutherAI to train large-scale language models. The original version of the dataset can be found here.
The dataset is divided into 22 smaller high-quality datasets. For more information each of them, please refer to the datasheet for the pile.
However, the current version of the dataset, available on the Hub, is not splitted accordingly. We had to solve this problem in order to improve the user experience when it comes to deal with the pile via the hub.
Here is an instance of the pile
{
'meta': {'pile_set_name': 'Pile-CC'},
'text': 'It is done, and submitted. You can play “Survival of the Tastiest” on Android, and on the web. Playing on...'
}
We used the meta column to properly divide the dataset in subsets. Each instance example belongs to the subset
domain and domain = example['meta']['pile_set_name']. By doing this, we were able to create a new version of the pile
that is properly divided, each instance having a new column domain.
We further splitted each subset in train/test (97%/3%) to build the current dataset which the following structure
data
ArXiv
train
test
BookCorpus2
train
test
Books3
train
test
Usage
from datasets import load_dataset
dataset = load_dataset(
"ArmelR/the-pile-splitted",
subset_of_interest,
num_proc=8
)
Using subset_of_interest = "default" will load the whole dataset.
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